{"id":"W4233862327","doi":"10.26434/chemrxiv.7607078.v1","title":"Accurate Kd via Transient Incomplete Separation","year":2019,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Superposition principle; Transient (computer programming); Dissociation (chemistry); Molecule; Constant (computer programming); Capillary action; Chemistry; Dissociation constant; Small molecule; Separation (statistics); Kinetic energy; Function (biology); Thermodynamics; Chemical physics; Chromatography; Analytical Chemistry (journal); Biological system; Computer science; Physics; Physical chemistry; Mathematics; Mathematical analysis; Classical mechanics; Organic chemistry; Statistics","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":[0.002292213,0.0008565163,0.001117289,0.0009028118,0.0008780462,0.001583322,0.002098754,0.001192792,0.001500188],"category_scores_gemma":[0.007994455,0.0008408401,0.0006130479,0.0008109199,0.001838256,0.003519849,0.001988246,0.002408631,0.0008126024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002475749,"about_ca_system_score_gemma":0.002357155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003573613,"about_ca_topic_score_gemma":0.002395772,"domain_scores_codex":[0.9984295,0.0002347678,0.00009059757,0.0004201092,0.0006964947,0.0001285731],"domain_scores_gemma":[0.9965641,0.001884238,0.0002903162,0.0007611607,0.0004192727,0.00008093496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005156812,0.0002530551,0.003989792,0.000873371,0.0001174509,0.0004672683,0.000787042,0.244787,0.2453181,0.3919067,0.004606244,0.1063782],"study_design_scores_gemma":[0.00002712831,0.00007553463,0.0003356363,0.00002317793,0.00001622364,0.0001278356,0.00003887474,0.827795,0.1163251,0.04916226,0.006015436,0.00005784785],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02837125,0.0004005344,0.9665021,0.0002894669,0.00008106846,0.00005075622,0.0001326192,0.001195489,0.002976714],"genre_scores_gemma":[0.588981,0.001255457,0.4020506,0.0005422755,0.00005702124,0.00036701,0.0004535345,0.0005789252,0.005714201],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003573613,"threshold_uncertainty_score":0.01796293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02285891108852151,"score_gpt":0.2779960828301136,"score_spread":0.2551371717415921,"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."}}