{"id":"W4415762809","doi":"10.1038/s44168-025-00307-5","title":"From pledges to places: action agendas need spatial data to integrate climate and biodiversity action","year":2025,"lang":"en","type":"letter","venue":"npj Climate Action","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Work & Health; Centre for Global Health Research; York University","funders":"HORIZON EUROPE Framework Programme; UK Research and Innovation; Deutsche Forschungsgemeinschaft; Economic and Social Research Council; European Climate, Infrastructure and Environment Executive Agency; European Commission; Government of Canada","keywords":"Action (physics); Biodiversity; Climate change; Citizen journalism; Spatial planning; Adaptation (eye); Global warming","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003343288,0.0005386673,0.0004746056,0.0002429127,0.0006091109,0.0003566638,0.0006775014,0.0007403156,0.01905622],"category_scores_gemma":[0.0001029983,0.0005515313,0.00009994715,0.0005041648,0.0001085029,0.0008128285,0.001672098,0.0009302667,0.005442993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001865053,"about_ca_system_score_gemma":0.0000221191,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01231768,"about_ca_topic_score_gemma":0.01158054,"domain_scores_codex":[0.9966437,0.0001710421,0.0004211053,0.001417969,0.000588393,0.0007577544],"domain_scores_gemma":[0.9983158,0.0001210081,0.0002995938,0.001002477,0.00004097689,0.0002201898],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003101902,0.00004982425,0.002414016,0.0001358774,0.00004581481,0.00002027321,0.000280525,0.00001054384,0.007855589,0.000001150975,0.9776453,0.01123091],"study_design_scores_gemma":[0.0004541252,0.0001099322,0.03264346,0.00009219012,0.0002111517,0.000007023898,0.003536343,0.0001809423,0.002498606,0.00001183128,0.959667,0.0005874553],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"commentary","genre_scores_codex":[0.6032361,0.00003897365,0.0009577323,0.3354371,0.008088947,0.001958095,0.04205547,0.0006967168,0.007530818],"genre_scores_gemma":[0.100684,0.01274149,0.001128041,0.6849121,0.008813812,0.0004255066,0.185207,0.0002551961,0.00583285],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.5025522,"threshold_uncertainty_score":0.9996936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1305369116448211,"score_gpt":0.3190554561256231,"score_spread":0.188518544480802,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}