{"id":"W2981573289","doi":"10.1021/acs.organomet.9b00563","title":"An Information-Rich Graphical Representation of Catalytic Cycles","year":2019,"lang":"en","type":"article","venue":"Organometallics","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Chemistry; Catalytic cycle; Catalysis; Representation (politics); Population; Reaction rate constant; Graphical user interface; Annotation; Kinetics; Computer science; Programming language; Organic chemistry; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008791938,0.00008711268,0.0001938667,0.0001504311,0.00002889228,0.00003701289,0.0001930445,0.00002585051,0.00107711],"category_scores_gemma":[0.000004146435,0.00008385,0.00008514968,0.0006555499,0.00003059869,0.0005029432,0.0000417326,0.00007212564,0.00009797188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009163385,"about_ca_system_score_gemma":0.00002154023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001165896,"about_ca_topic_score_gemma":0.000003651696,"domain_scores_codex":[0.9993053,0.00002467633,0.000278526,0.0001158958,0.0001633284,0.0001122702],"domain_scores_gemma":[0.9992577,0.00003541877,0.0001546908,0.0004145185,0.00009389352,0.00004375509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009578304,0.0001923435,0.8553232,0.00002072081,0.0001787804,1.250448e-7,0.0004904963,0.0004883911,0.005800892,0.1110142,0.00024008,0.02624125],"study_design_scores_gemma":[0.001914101,0.0005105915,0.689511,0.00006514573,0.0006461755,0.000003288684,0.003210288,0.03380697,0.143771,0.1090114,0.01593092,0.001619127],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.979669,0.00000621054,0.01231429,0.00003184467,0.00002818067,0.0001416044,0.00001214678,0.00004430247,0.007752355],"genre_scores_gemma":[0.9978774,0.000002537299,0.00164992,0.00001684769,0.00004582255,0.000006417197,0.0003249131,0.000008457653,0.00006767346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1658122,"threshold_uncertainty_score":0.999836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008432823466653413,"score_gpt":0.2653788683581322,"score_spread":0.2569460448914788,"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."}}