{"id":"W4251621304","doi":"10.1515/iupac.87.0336","title":"Kainic Acid","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Animal testing and alternatives","field":"Veterinary","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Psychology; Chemistry; Linguistics; Philosophy; Organic chemistry; Data mining","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":[0.0004934866,0.0005030365,0.0006188038,0.0001688216,0.0001386281,0.00006264653,0.0006556288,0.0002936274,0.006284771],"category_scores_gemma":[0.001059592,0.000364019,0.0002152377,0.0001208116,0.0001891058,0.00009710715,0.0003158793,0.0005821199,0.00004124398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002568584,"about_ca_system_score_gemma":0.0003930929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009216314,"about_ca_topic_score_gemma":0.00006995157,"domain_scores_codex":[0.9973916,0.000140015,0.0004707388,0.0006465697,0.0008507405,0.000500374],"domain_scores_gemma":[0.9981542,0.0001977485,0.0003450604,0.0008329834,0.0002992324,0.0001707282],"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":[0.0004765309,0.0001448467,0.00001011147,0.0001051428,0.0001138661,0.000582351,0.00001189438,4.480803e-8,0.0001254548,0.00001034623,0.9936439,0.004775537],"study_design_scores_gemma":[0.0006362111,0.001600669,0.00005999859,0.0007414853,0.00007235443,0.0001297135,0.00002236271,0.000003057925,0.00002016406,0.0002670203,0.9959506,0.0004964129],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001082091,0.0009294229,0.00008556608,0.0002506981,0.0007400819,0.000168712,0.9961575,0.0002146392,0.0003712836],"genre_scores_gemma":[0.0006866035,0.0004297997,0.0001185883,0.0002296693,0.002225388,0.00001353032,0.9950477,0.0000645059,0.001184221],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.006243527,"threshold_uncertainty_score":0.9998811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1061497864984377,"score_gpt":0.5121859203992433,"score_spread":0.4060361339008056,"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."}}