{"id":"W4251652633","doi":"10.1515/iupac.87.0646","title":"Synaptic Stripping","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","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; Neuroscience; Psychology; Chemistry; Linguistics; Data mining; Philosophy; 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":[0.001021732,0.002524017,0.001553222,0.004410983,0.001574404,0.003638708,0.003502292,0.002228363,0.1120494],"category_scores_gemma":[0.008697034,0.0007609185,0.002952464,0.004994115,0.0005240481,0.002420278,0.002956255,0.002334463,0.1707704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001429228,"about_ca_system_score_gemma":0.003244066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02234196,"about_ca_topic_score_gemma":0.05567062,"domain_scores_codex":[0.9987698,0.0001483158,0.0002092199,0.0004018148,0.0002711824,0.0001996221],"domain_scores_gemma":[0.9970372,0.0006752177,0.0002173903,0.001124177,0.0007682922,0.0001778353],"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":[0.0001679557,0.00003117815,0.002022206,0.001451114,0.00008348846,0.00007334293,0.00003138452,0.0004683267,0.0002372244,0.0009110334,0.9803556,0.01416713],"study_design_scores_gemma":[0.0001923381,0.00003805076,0.005984099,0.0007122448,0.0000883645,0.0002375906,0.0001089921,0.0009772583,0.0009334408,0.004209817,0.9864725,0.00004514238],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004464909,0.0005040129,0.0004149599,0.0001521335,0.0001400166,0.00004255633,0.9930427,0.001693174,0.00356404],"genre_scores_gemma":[0.001248544,0.0003314396,0.001054461,0.0001245105,0.00002191496,0.0001235656,0.9945152,0.0001863381,0.002393975],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1120494,"threshold_uncertainty_score":0.3748427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01449514385001241,"score_gpt":0.3800567363685923,"score_spread":0.3655615925185799,"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."}}