{"id":"W4252016773","doi":"10.1515/iupac.81.0431","title":"Habitat","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Ecology; Relation (database); Habitat; Computer science; Biology; Data mining; Linguistics; Philosophy","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":[0.0008983202,0.001281148,0.001141339,0.003123797,0.0009449408,0.00307315,0.002386596,0.001655552,0.2147786],"category_scores_gemma":[0.007981385,0.0005192172,0.0009273593,0.007034997,0.0003803547,0.002643171,0.002571476,0.001731113,0.2650304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001434602,"about_ca_system_score_gemma":0.002076132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0195068,"about_ca_topic_score_gemma":0.04695117,"domain_scores_codex":[0.998638,0.0002442563,0.0001771437,0.0004340593,0.0003199767,0.00018651],"domain_scores_gemma":[0.9970031,0.00070566,0.0002848161,0.0007315279,0.0009986497,0.0002763282],"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":[0.00003223453,0.000007889278,0.0009018122,0.000416114,0.00001006762,0.00001369312,0.00002462788,0.00009726006,0.00004113995,0.0007469366,0.9942288,0.003479373],"study_design_scores_gemma":[0.00004437804,0.000005065625,0.001696421,0.0002848037,0.000007845308,0.00003295113,0.00008615338,0.0001066394,0.00007757579,0.001087591,0.9965587,0.00001179948],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008341332,0.00006641479,0.00007173177,0.00009812812,0.00003255528,0.00001054541,0.9974142,0.000202525,0.002020421],"genre_scores_gemma":[0.000334071,0.00007860444,0.0002980234,0.0001021002,0.000009196151,0.00005707121,0.9973609,0.00008195635,0.001678069],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2147786,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01621476810320666,"score_gpt":0.4169834246330821,"score_spread":0.4007686565298754,"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."}}