{"id":"W4235225866","doi":"10.1515/iupac.79.1253","title":"Eutrophication","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Library science; Chemistry; Philosophy; Biology; Linguistics","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":[0.0009571221,0.001849224,0.001603933,0.00312694,0.0006310353,0.002248836,0.002001719,0.001204035,0.06120997],"category_scores_gemma":[0.005069795,0.0005234767,0.001803328,0.005339722,0.000291978,0.001283511,0.001759682,0.001450958,0.06841593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001216571,"about_ca_system_score_gemma":0.002001006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02052682,"about_ca_topic_score_gemma":0.03861076,"domain_scores_codex":[0.9986945,0.0001820487,0.0002133506,0.0004929426,0.0002919282,0.0001252311],"domain_scores_gemma":[0.9979801,0.000457421,0.0003605669,0.0004514998,0.0006102428,0.0001402365],"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":[0.0001723621,0.00002660779,0.005414308,0.002479047,0.0001468474,0.00003757667,0.00003513769,0.0005863809,0.0002771635,0.0009357958,0.9813177,0.00857117],"study_design_scores_gemma":[0.000195109,0.00001977836,0.01145488,0.0006236924,0.00008545568,0.00008073038,0.00006756872,0.0003485523,0.0003611669,0.001072083,0.9856539,0.00003705738],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001606679,0.0001238268,0.00005471609,0.00003339035,0.000020865,0.000007760347,0.9987304,0.0001094775,0.0007588713],"genre_scores_gemma":[0.0005942486,0.000140442,0.0002811486,0.00006244825,0.000007944584,0.00005736123,0.9979413,0.00004375648,0.000871369],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06120997,"threshold_uncertainty_score":0.2047678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01322739949379016,"score_gpt":0.3898747927873776,"score_spread":0.3766473932935875,"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."}}