{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001366533,0.0009614173,0.001233808,0.0006030002,0.0001629081,0.0001091193,0.001260439,0.0007821139,0.02539111],"category_scores_gemma":[0.001835574,0.0007223829,0.0003913966,0.0004682071,0.0003751393,0.0001829628,0.0004536702,0.000946984,0.0005614068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001655015,"about_ca_system_score_gemma":0.001871906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001889541,"about_ca_topic_score_gemma":0.001614094,"domain_scores_codex":[0.9940273,0.0002419086,0.0008411502,0.001062433,0.002777997,0.001049225],"domain_scores_gemma":[0.9952297,0.0001865311,0.0006385763,0.002504936,0.0009987726,0.0004414427],"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":[0.000331017,0.0003216651,0.000003751459,0.0001335139,0.0002255446,0.0002580819,0.000004468453,5.672326e-7,0.00003136529,0.00001340755,0.9961574,0.002519188],"study_design_scores_gemma":[0.001628596,0.0002144133,0.00001856407,0.0007403754,0.0002668772,0.00004617891,0.000007233816,0.000001308334,0.00002897913,0.000318313,0.9957705,0.0009586635],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001918628,0.00108244,0.00004662885,0.0004247509,0.001414807,0.0004899262,0.9959487,0.0003686564,0.0002048812],"genre_scores_gemma":[0.000003250254,0.0005286034,0.00005576708,0.0002889789,0.002652779,0.00003025398,0.9948754,0.000294913,0.001270024],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0248297,"threshold_uncertainty_score":0.9995227,"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."}}