{"id":"W2577559092","doi":"10.29007/493z","title":"Modeling Organic Chemistry and Planning Organic Synthesis","year":2018,"lang":"en","type":"article","venue":"EPiC series in computing","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Benchmark (surveying); Set (abstract data type); Domain (mathematical analysis); Organic molecules; Artificial intelligence; Theoretical computer science; Chemistry; Programming language; Molecule; Mathematics; Organic chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0003553632,0.0001449346,0.0002123028,0.00004130355,0.0002099224,0.0001429936,0.0005529327,0.00007754136,0.00005766654],"category_scores_gemma":[0.0005852241,0.0001432455,0.00001960035,0.0003187193,0.00009678853,0.0002740093,0.0006121675,0.0001452442,0.0000104747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000036803,"about_ca_system_score_gemma":0.0000482939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002160279,"about_ca_topic_score_gemma":0.00001250475,"domain_scores_codex":[0.9988397,0.00003802986,0.0002556357,0.0004016252,0.0001267555,0.0003382826],"domain_scores_gemma":[0.9992411,0.0002468617,0.00005555243,0.0003568093,0.00005319906,0.00004654902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001328261,0.0003070436,0.2222209,0.001138851,0.0003078517,0.001004431,0.100107,0.01373571,0.1175722,0.01837389,0.0005974175,0.5245019],"study_design_scores_gemma":[0.0001672817,0.00002969807,0.002902807,0.0002164774,0.000005445271,0.0001550917,0.001497294,0.9714831,0.02029715,0.002876598,0.00007627194,0.0002928353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7102782,0.0002871246,0.2874819,0.0002552251,0.0003035105,0.00003570892,9.24539e-8,0.0001907064,0.001167455],"genre_scores_gemma":[0.9572561,0.000009970561,0.04232092,0.000107701,0.0002594095,0.000001292824,2.148695e-7,0.00001040136,0.00003399579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9577473,"threshold_uncertainty_score":0.5841383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02047545171841846,"score_gpt":0.2535248274359482,"score_spread":0.2330493757175297,"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."}}