{"id":"W2074027356","doi":"10.1002/chin.200644241","title":"High Throughput Screening Methods for Asymmetric Synthesis","year":2006,"lang":"en","type":"article","venue":"ChemInform","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Chemistry; Throughput; Service (business); Combinatorial chemistry; Nanotechnology; Telecommunications; Computer science; Business","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":[0.001492847,0.001154942,0.001393516,0.002484842,0.0006678597,0.0009479355,0.001535733,0.0006249839,0.01565341],"category_scores_gemma":[0.001791451,0.0007014995,0.0008862764,0.001524989,0.0005224322,0.00105767,0.001299082,0.00158176,0.007306242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008154134,"about_ca_system_score_gemma":0.0006261518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005989455,"about_ca_topic_score_gemma":0.001336466,"domain_scores_codex":[0.9980578,0.0003867113,0.00009170543,0.0002380823,0.001085053,0.0001405929],"domain_scores_gemma":[0.9992375,0.0003336199,0.00006694208,0.0001465995,0.0001674955,0.00004788051],"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":[0.0007357835,0.0007547576,0.0004338649,0.001857449,0.0001718581,0.0003774473,0.0001014204,0.004586007,0.6767756,0.01036458,0.0191145,0.2847268],"study_design_scores_gemma":[0.0002584707,0.001221123,0.0009051223,0.00009057017,0.0001542276,0.000732563,0.00005849428,0.02118453,0.9244385,0.005390255,0.04546313,0.0001030321],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1100171,0.02500859,0.7748294,0.001661607,0.001114116,0.004028669,0.01193422,0.008199938,0.06320624],"genre_scores_gemma":[0.5441644,0.02834675,0.357744,0.0009258008,0.0003689365,0.00411135,0.01359123,0.0007770061,0.04997049],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01565341,"threshold_uncertainty_score":0.05236584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01929451614706962,"score_gpt":0.3195175089660366,"score_spread":0.300222992818967,"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."}}