{"id":"W4253024774","doi":"10.1515/iupac.83.0360","title":"End-Point Assay","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Glossary; Context (archaeology); Computer science; Field (mathematics); Multidisciplinary approach; Process (computing); Data science; Point (geometry); Component (thermodynamics); Management science; Sociology; Engineering; Biology; Linguistics; Mathematics","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":[0.003167043,0.002597152,0.002503498,0.003361436,0.001023794,0.003656515,0.004028973,0.002294265,0.04426132],"category_scores_gemma":[0.01285061,0.0007494303,0.002186096,0.004793278,0.0006242368,0.001684322,0.002275446,0.003589824,0.08676429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001798264,"about_ca_system_score_gemma":0.002689246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007459814,"about_ca_topic_score_gemma":0.01421689,"domain_scores_codex":[0.9959276,0.0005672451,0.0007743991,0.00111496,0.001239601,0.0003760785],"domain_scores_gemma":[0.9918827,0.002008489,0.001142176,0.002423795,0.002124214,0.000418608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001107995,0.000212334,0.009818732,0.003210003,0.0001594074,0.0001182119,0.00005322631,0.001382351,0.001102392,0.002738523,0.9587693,0.02132742],"study_design_scores_gemma":[0.0004744884,0.0001532134,0.01232089,0.0007975685,0.000140896,0.000316427,0.00008104522,0.001278858,0.003385779,0.004242916,0.9767069,0.0001010255],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009605399,0.0003977932,0.00110132,0.00009541557,0.00007746615,0.0001418108,0.9929253,0.001125743,0.003174594],"genre_scores_gemma":[0.001458385,0.0002190663,0.001790048,0.000147895,0.00001623693,0.0004226929,0.9943902,0.000133405,0.001422082],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04426132,"threshold_uncertainty_score":0.1480688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01942044355542093,"score_gpt":0.4211968339502035,"score_spread":0.4017763903947825,"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."}}