{"id":"W4390046068","doi":"10.1126/science.adn3245","title":"A landmark environmental law looks ahead","year":2023,"lang":"en","type":"article","venue":"Science","topic":"Conservation, Ecology, Wildlife Education","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Endangered species; Looming; Environmental law; Political science; Environmental ethics; Landmark; Geography; Law; Ecology; Habitat; Biology; Cartography; Psychology","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007425529,0.00007973624,0.00006240968,0.00005736064,0.0004399525,0.0000463044,0.0004186426,0.00003110737,0.002002942],"category_scores_gemma":[0.00008026129,0.00007856231,0.00002114815,0.0007871067,0.001306431,0.000440982,0.0002677697,0.00006880536,0.008955964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002718234,"about_ca_system_score_gemma":0.00004152306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001644058,"about_ca_topic_score_gemma":0.0004192989,"domain_scores_codex":[0.9986892,0.00002501935,0.0001289182,0.0003866678,0.0004055992,0.0003645975],"domain_scores_gemma":[0.9994775,0.00005986679,0.00004502061,0.0002955896,0.000002951851,0.0001190665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003231457,0.00005071217,0.9401464,0.000001579918,0.000001305663,0.000003325121,0.0007301373,0.0001809236,0.04790974,0.0006448195,0.007308319,0.003019434],"study_design_scores_gemma":[0.00008607424,0.00002155858,0.9445896,0.000002072537,0.000002118029,0.000005429876,0.0001673988,0.001046492,0.001086044,0.001404709,0.05148688,0.0001016186],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9798806,0.000005559764,0.00001833358,0.002004334,0.0004715334,0.0001416896,0.000004202986,0.00009710026,0.0173767],"genre_scores_gemma":[0.9953995,0.000006568185,0.0003692913,0.001075935,0.00004339018,0.00002498495,0.000006162815,0.000006392844,0.003067734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0468237,"threshold_uncertainty_score":0.9989094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01296417357911478,"score_gpt":0.2480741783621827,"score_spread":0.235110004783068,"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."}}