{"id":"W1983921911","doi":"10.1002/adsc.200800596","title":"Time as a Dimension in High‐Throughput Homogeneous Catalysis","year":2008,"lang":"en","type":"article","venue":"Advanced Synthesis & Catalysis","topic":"Synthetic Organic Chemistry Methods","field":"Chemistry","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Throughput; Chemistry; Catalysis; Homogeneous; Quenching (fluorescence); Selectivity; Dimension (graph theory); High-throughput screening; Productivity; Homogeneous catalysis; Combinatorial chemistry; Computational chemistry; Nanotechnology; Organic chemistry; Computer science; Statistical physics; Physics; Quantum mechanics; Telecommunications","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004116348,0.0006787883,0.001262944,0.0002536781,0.0002982722,0.00002709105,0.0008241553,0.0003890792,0.006919038],"category_scores_gemma":[0.002702843,0.0007146857,0.0004914971,0.001187044,0.0003907214,0.0002747981,0.0003076828,0.0003851324,0.001435643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005797879,"about_ca_system_score_gemma":0.0001749287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005586139,"about_ca_topic_score_gemma":0.00004629784,"domain_scores_codex":[0.9958128,0.0001179793,0.0009683676,0.001442339,0.0007791834,0.0008793283],"domain_scores_gemma":[0.9953067,0.001596385,0.0003801324,0.002295172,0.0001227522,0.000298905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009820729,0.0003817907,0.0005384422,0.00006329911,0.0002722045,0.0005268274,0.0005163046,0.0004334197,0.9672555,0.00000484709,0.00008634771,0.02982278],"study_design_scores_gemma":[0.0005594849,0.00001342289,0.000147382,0.0001184238,0.0004161011,0.0004930932,0.0003005453,0.0002600109,0.9942457,0.000136017,0.002513146,0.0007966625],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914117,0.0008855165,0.0001060198,0.0003030325,0.00007032347,0.0001126899,0.00005105255,0.000328831,0.006730779],"genre_scores_gemma":[0.9818217,0.0004490369,0.01159934,0.00007219455,0.0001411989,0.0001839923,0.000161043,0.0001584056,0.005413138],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02902611,"threshold_uncertainty_score":0.9995304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008769527008538558,"score_gpt":0.2398300539409525,"score_spread":0.2310605269324139,"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."}}