{"id":"W4365147174","doi":"10.1515/iupac.94.0822","title":"Silylene","year":2023,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemical Reactions and Mechanisms","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Terminology; Abandonment (legal); Meaning (existential); Field (mathematics); Computer science; Chemistry; Linguistics; Epistemology; Philosophy; Mathematics; Political science","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":[0.0006485676,0.00260671,0.001582865,0.003122446,0.0009793302,0.002411517,0.002368301,0.001636749,0.1571812],"category_scores_gemma":[0.00261689,0.0006962857,0.001479663,0.004848585,0.0003764776,0.002119091,0.001881242,0.001817473,0.2502324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001157159,"about_ca_system_score_gemma":0.001599484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01116708,"about_ca_topic_score_gemma":0.02648476,"domain_scores_codex":[0.9991416,0.0001144572,0.00009172825,0.000306196,0.00022911,0.0001168195],"domain_scores_gemma":[0.9991307,0.000236432,0.0001259948,0.0002398838,0.0001965335,0.00007052821],"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":[0.0001176193,0.00003218592,0.0005731549,0.001566972,0.00003313824,0.00003452427,0.00002196699,0.0003047623,0.0006462152,0.0008701242,0.9864245,0.009374924],"study_design_scores_gemma":[0.0000903758,0.00002632292,0.002449623,0.0003109282,0.00003051017,0.00008503927,0.00004453192,0.0003540705,0.0008364349,0.001674169,0.9940678,0.0000300606],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002781534,0.0003512067,0.0002118541,0.00005948832,0.00004110027,0.00002056185,0.9949044,0.0007626821,0.003370528],"genre_scores_gemma":[0.0003296513,0.0002066193,0.0003487135,0.00006465214,0.000006150197,0.00005143465,0.9974521,0.0000927111,0.001447923],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1571812,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01708526887649986,"score_gpt":0.3969886015345837,"score_spread":0.3799033326580838,"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."}}