{"id":"W4409001582","doi":"10.1021/acscatal.5c01051","title":"Evaluating Predictive Accuracy in Asymmetric Catalysis: A Machine Learning Perspective on Local Reaction Space","year":2025,"lang":"en","type":"article","venue":"ACS Catalysis","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Canada Foundation for Innovation; Compute Canada","keywords":"Perspective (graphical); Catalysis; Space (punctuation); Computer science; Artificial intelligence; Machine learning; Chemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007710416,0.001130396,0.001858965,0.00156856,0.000631755,0.001596359,0.001737991,0.001297275,0.0007438209],"category_scores_gemma":[0.02278675,0.0003753625,0.001031189,0.001310325,0.001636319,0.002913794,0.001503135,0.002135285,0.0003191498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009688256,"about_ca_system_score_gemma":0.0008939808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002660959,"about_ca_topic_score_gemma":0.002069501,"domain_scores_codex":[0.997277,0.001480493,0.0001158294,0.0004131361,0.0005766411,0.0001370544],"domain_scores_gemma":[0.9863511,0.01042652,0.0009649756,0.001449721,0.0006169928,0.0001908032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001088042,0.00006224757,0.003464503,0.00009095677,0.00006447008,0.00003635948,0.00003908157,0.9646796,0.001517857,0.008896015,0.0003396525,0.02070046],"study_design_scores_gemma":[0.000006238226,0.00007250612,0.0003377588,0.00001766841,0.00001165207,0.00001503967,0.00001074322,0.9898937,0.001655628,0.007776354,0.0001921305,0.00001049094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.389941,0.005207632,0.595722,0.001613518,0.00008348018,0.0001046938,0.0005168986,0.001467783,0.005342895],"genre_scores_gemma":[0.9503691,0.00108836,0.04728175,0.000154802,0.0000709703,0.00006930261,0.0004834669,0.00009804415,0.0003842479],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007710416,"threshold_uncertainty_score":0.04077703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01633734807414434,"score_gpt":0.3389765865760966,"score_spread":0.3226392385019523,"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."}}