{"id":"W4247607227","doi":"10.1515/iupac.81.0341","title":"Epifauna","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; Relation (database); Ecology; 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":[0.001189201,0.001756541,0.00140898,0.007246088,0.00113563,0.004862858,0.002238733,0.001590671,0.1800666],"category_scores_gemma":[0.0134246,0.0006647424,0.001234963,0.01512448,0.0004902839,0.003449449,0.003213882,0.001796145,0.1815598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00210442,"about_ca_system_score_gemma":0.004278583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02936973,"about_ca_topic_score_gemma":0.04431698,"domain_scores_codex":[0.9983428,0.0002894806,0.0002358188,0.0004843138,0.0003929015,0.0002548424],"domain_scores_gemma":[0.9955742,0.001259093,0.0004962409,0.0008616464,0.001413421,0.0003954898],"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":[0.00006108035,0.000007342827,0.001113596,0.001791413,0.00002889569,0.00002512048,0.00005409067,0.000156463,0.0001061612,0.001338044,0.9880145,0.0073033],"study_design_scores_gemma":[0.00003348253,0.000005949854,0.001894507,0.0004999368,0.00001353382,0.00003170812,0.00006860362,0.0000824974,0.00007051775,0.001110266,0.9961761,0.00001284287],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001042856,0.0002561007,0.0000727942,0.0001854827,0.00004238591,0.000009414911,0.997177,0.0002785552,0.001873997],"genre_scores_gemma":[0.0004802748,0.0003216985,0.0002485678,0.0001199449,0.00001623909,0.00007041376,0.9967868,0.0001049296,0.001851115],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1800666,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01691646503829011,"score_gpt":0.4293296780270259,"score_spread":0.4124132129887358,"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."}}