{"id":"W4249417077","doi":"10.32920/ryerson.14654637.v1","title":"Organic chemistry synthesis problem as artificial intelligence planning","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Planner; Benchmark (surveying); Computer science; Field (mathematics); Organic synthesis; Artificial intelligence; Chemistry; Organic chemistry; Mathematics; Catalysis","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":[0.0008040545,0.0006481892,0.0004727073,0.0005498996,0.0008418446,0.001814392,0.001141667,0.001689913,0.008131352],"category_scores_gemma":[0.002076276,0.0003334285,0.0009104039,0.0009008367,0.001879848,0.002749985,0.00116637,0.001699389,0.0006561883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002056609,"about_ca_system_score_gemma":0.002831853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007006343,"about_ca_topic_score_gemma":0.00785796,"domain_scores_codex":[0.9992274,0.000297915,0.00003753476,0.0001632906,0.0002074493,0.00006632196],"domain_scores_gemma":[0.9992319,0.000561033,0.0000527961,0.00006435014,0.00005431009,0.00003554671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005758048,0.00006058804,0.0002299684,0.000177189,0.00002810381,0.0002005772,0.0001399806,0.3801648,0.001233026,0.5663549,0.005286677,0.04606667],"study_design_scores_gemma":[0.00006668357,0.00004398017,0.0001459751,0.00006115331,0.00002848024,0.0001376062,0.0002130286,0.4623964,0.002389733,0.4822471,0.0522455,0.00002432007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02361212,0.0007847419,0.8983458,0.00469363,0.0002308697,0.0003030266,0.0005506473,0.0005014265,0.07097764],"genre_scores_gemma":[0.2898356,0.001612289,0.67998,0.0006129322,0.0001163129,0.000350285,0.0009033558,0.0001269321,0.02646221],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008131352,"threshold_uncertainty_score":0.02720207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04773138616923248,"score_gpt":0.2847792280651384,"score_spread":0.2370478418959059,"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."}}