{"id":"W4282968134","doi":"10.1126/science.add3070","title":"Broaden chemicals scope in biodiversity targets","year":2022,"lang":"en","type":"letter","venue":"Science","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Scope (computer science); Biodiversity; Business; Environmental resource management; Environmental planning; Environmental science; Ecology; Biology; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004875196,0.0009617419,0.00085751,0.002022122,0.003727038,0.006567379,0.002092993,0.02512564,0.08863871],"category_scores_gemma":[0.02440818,0.0008701904,0.00133275,0.001566749,0.001821418,0.004625154,0.005129675,0.01465523,0.05058441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006459856,"about_ca_system_score_gemma":0.008655222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01759798,"about_ca_topic_score_gemma":0.0664142,"domain_scores_codex":[0.9922547,0.0005509311,0.0003522225,0.0006352579,0.005283726,0.0009230726],"domain_scores_gemma":[0.9865708,0.004583158,0.0006281292,0.0009467204,0.005035127,0.002236054],"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":[0.00001951001,0.00002480225,0.0001932923,0.00003596224,0.000004149875,0.00008355573,0.00002017195,0.00004612657,0.0002162759,0.006939412,0.9730628,0.01935408],"study_design_scores_gemma":[0.00002038388,0.00002659599,0.0006907451,0.00007834147,0.000006314488,0.00009380995,0.00005362996,0.0001486654,0.0003317634,0.005505394,0.9930321,0.00001230189],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.002059322,0.002596647,0.002030163,0.6015878,0.02530111,0.0001377606,0.001937652,0.001412106,0.3629375],"genre_scores_gemma":[0.01329633,0.001198702,0.001985355,0.6022841,0.009115309,0.0001641278,0.0008118786,0.0003805612,0.3707637],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.08863871,"threshold_uncertainty_score":0.296526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02453274504856462,"score_gpt":0.2672203638263472,"score_spread":0.2426876187777826,"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."}}