{"id":"W4255098797","doi":"10.1515/iupac.79.0728","title":"Abiotic","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; Chemical nomenclature; Terminology; Toxicology; Computer science; Chemistry; Biology; Philosophy; Linguistics; Organic chemistry","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":[0.001369732,0.001804512,0.001388047,0.003382444,0.001126045,0.00364637,0.002647074,0.001641372,0.1902094],"category_scores_gemma":[0.01097696,0.0005464392,0.001829097,0.00626201,0.0003720231,0.002755382,0.002172535,0.001660511,0.2407771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001671932,"about_ca_system_score_gemma":0.002743059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02188456,"about_ca_topic_score_gemma":0.03471985,"domain_scores_codex":[0.9975054,0.000402115,0.0003774028,0.0009138555,0.0005396783,0.0002616927],"domain_scores_gemma":[0.9956269,0.0009901326,0.0004212072,0.001134182,0.001569449,0.0002580805],"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":[0.0001035248,0.00001875982,0.001804653,0.0007641843,0.00003914754,0.00002308611,0.00002826342,0.0001679495,0.00008482725,0.0008963727,0.9873073,0.008761985],"study_design_scores_gemma":[0.00009548855,0.00001433318,0.003624561,0.0003936272,0.00003245939,0.00005650931,0.0001085239,0.0001851779,0.0001565413,0.00147987,0.9938287,0.00002425663],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001791171,0.0001281702,0.0001689846,0.0001127821,0.000057178,0.00003143137,0.9960331,0.0003115268,0.002977622],"genre_scores_gemma":[0.0005650053,0.00011595,0.0004269228,0.0001913311,0.00001756668,0.0001420517,0.9956836,0.00009786942,0.002759785],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1902094,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01571236141435402,"score_gpt":0.4204527635704782,"score_spread":0.4047404021561242,"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."}}