Datasets:

ClarusC64
/

climate-resilient-basin-gradient-intervention-mapping-v0.1

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 3 new columns ({'from dataclasses import dataclass', '__index_level_1__', '__index_level_0__'}) and 16 missing columns ({'basin_gradient_vector', 'projected_coherence_gain', 'notes', 'tradeoff_profile', 'current_basin_estimate', 'time_window', 'projected_mechanisms', 'uncertainty_sources', 'target_resilient_basin', 'system_state_summary', 'candidate_interventions', 'leverage_points_ranked', 'monitoring_signals', 'id', 'gold_checklist', 'constraints'}).

This happened while the csv dataset builder was generating data using

hf://datasets/ClarusC64/climate-resilient-basin-gradient-intervention-mapping-v0.1/data/test.csv (at revision 0e0ca68f2da12ad19c6e2775303e11c6a6bb05ee), [/tmp/hf-datasets-cache/medium/datasets/62657916673813-config-parquet-and-info-ClarusC64-climate-resilie-556013d5/hub/datasets--ClarusC64--climate-resilient-basin-gradient-intervention-mapping-v0.1/snapshots/0e0ca68f2da12ad19c6e2775303e11c6a6bb05ee/data/test.csv (origin=hf://datasets/ClarusC64/climate-resilient-basin-gradient-intervention-mapping-v0.1@0e0ca68f2da12ad19c6e2775303e11c6a6bb05ee/data/test.csv)]

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 674, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              from dataclasses import dataclass: string
              __index_level_0__: string
              __index_level_1__: string
              -- schema metadata --
              pandas: '{"index_columns": ["__index_level_0__", "__index_level_1__"], "c' + 638
              to
              {'id': Value('string'), 'time_window': Value('string'), 'current_basin_estimate': Value('string'), 'target_resilient_basin': Value('string'), 'system_state_summary': Value('string'), 'candidate_interventions': Value('string'), 'projected_mechanisms': Value('string'), 'basin_gradient_vector': Value('string'), 'leverage_points_ranked': Value('string'), 'projected_coherence_gain': Value('string'), 'tradeoff_profile': Value('string'), 'monitoring_signals': Value('string'), 'uncertainty_sources': Value('string'), 'notes': Value('string'), 'constraints': Value('string'), 'gold_checklist': Value('string')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1736, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1889, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 3 new columns ({'from dataclasses import dataclass', '__index_level_1__', '__index_level_0__'}) and 16 missing columns ({'basin_gradient_vector', 'projected_coherence_gain', 'notes', 'tradeoff_profile', 'current_basin_estimate', 'time_window', 'projected_mechanisms', 'uncertainty_sources', 'target_resilient_basin', 'system_state_summary', 'candidate_interventions', 'leverage_points_ranked', 'monitoring_signals', 'id', 'gold_checklist', 'constraints'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/ClarusC64/climate-resilient-basin-gradient-intervention-mapping-v0.1/data/test.csv (at revision 0e0ca68f2da12ad19c6e2775303e11c6a6bb05ee), [/tmp/hf-datasets-cache/medium/datasets/62657916673813-config-parquet-and-info-ClarusC64-climate-resilie-556013d5/hub/datasets--ClarusC64--climate-resilient-basin-gradient-intervention-mapping-v0.1/snapshots/0e0ca68f2da12ad19c6e2775303e11c6a6bb05ee/data/test.csv (origin=hf://datasets/ClarusC64/climate-resilient-basin-gradient-intervention-mapping-v0.1@0e0ca68f2da12ad19c6e2775303e11c6a6bb05ee/data/test.csv)]
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

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id string	time_window string	current_basin_estimate string	target_resilient_basin string	system_state_summary string	candidate_interventions string	projected_mechanisms string	basin_gradient_vector string	leverage_points_ranked string	projected_coherence_gain string	tradeoff_profile string	monitoring_signals string	uncertainty_sources string	notes string	constraints string	gold_checklist string
RBGIM-001	reference_stable	holocene_like_stable	holocene_like_stable	Energy balance near zero; tight coupling; low variance	maintain low forcing; protect sinks	preserve coupling; avoid shocks	flat	protect forests > reduce methane > reduce soot	Low	low tradeoffs	ocean heat; land sink strength; albedo	proxy sparsity	Baseline mapping case	Under 300 words.	target+vector+levers+gain+tradeoffs
RBGIM-002	modern_transition	warming_transition	holocene_like_stable	Positive energy imbalance; ocean heat up; cryosphere loss; coupling weakening	methane cuts; soot cuts; rapid renewables; forest protection	fast forcing reduction; albedo relief; sink preservation	moderate_toward_resilient	methane > soot > coal phaseout > forest protection	Medium	air quality gains; food system pressure	CH4; aerosol forcing; sea ice; land sink	forcing attribution	Fast levers first	Under 300 words.	target+vector+levers+gain+tradeoffs
RBGIM-003	modern_transition	warming_transition	holocene_like_stable	Regional drought clustering; soil moisture variance high; biosphere stress	restoration corridors; soil carbon; irrigation reform	raise land resilience; reduce variance; strengthen coupling	moderate_toward_resilient	soil moisture management > restoration > water policy	Low to Medium	water tradeoffs; land use conflict	soil moisture; VPD; vegetation stress	regional coverage gaps	Land-first gradient	Under 300 words.	target+vector+levers+gain+tradeoffs
RBGIM-004	high_risk_edge	hothouse_risk	holocene_like_stable	Coherence loss index high; cryosphere threshold signals	methane cuts; soot cuts; emergency demand reduction	lower short-lived forcing quickly	steep_toward_resilient_if_fast	methane > soot > demand reduction	Medium to High	economic disruption risk	CH4; Arctic melt timing; jet metrics	model spread on thresholds	Urgency case	Under 300 words.	target+vector+levers+gain+tradeoffs
RBGIM-005	high_risk_edge	hothouse_risk	holocene_like_stable	Heat extremes rising; ocean heat high; resilience margin narrow	SRM pilot; methane cuts; marine cloud brightening study	albedo intervention plus forcing cuts	steep_but_high_uncertainty	methane > SRM pilot governance > soot	Medium	risk of regional mismatch; governance risk	regional precipitation; aerosol optical depth; ocean heat	governance unknowns	Shows tradeoff structure	Under 300 words.	target+vector+levers+gain+tradeoffs
RBGIM-006	transition_with_policy	warming_transition	holocene_like_stable	Emissions plateau; land sink weakening; coupling strain	deforestation halt; methane cuts; grid buildout	sink stabilisation plus forcing cuts	moderate_toward_resilient	deforestation halt > methane > grid buildout	Medium	food prices; supply chain strain	land sink; CH4; CO2 growth rate	reporting lag	Sink is the hinge	Under 300 words.	target+vector+levers+gain+tradeoffs

What this dataset tests

Map the gradient from the current basin
toward a more resilient basin
and rank intervention levers by coherence gain.

Required outputs

target resilient basin
basin gradient vector
ranked leverage points
projected coherence gain
tradeoff profile
monitoring signals

Use case

Third layer of Planetary Basin Transition Maps.

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