{"id":"W4239817749","doi":"10.1515/iupac.88.0407","title":"Adhesion Factor","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Coagulation, Bradykinin, Polyphosphates, and Angioedema","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","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":[0.001157599,0.001291257,0.001508883,0.003778408,0.0007413176,0.002696489,0.001795985,0.001627798,0.09623908],"category_scores_gemma":[0.01199647,0.0005425926,0.001829343,0.005845517,0.0002881737,0.001805358,0.00153878,0.001750849,0.07087079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009494125,"about_ca_system_score_gemma":0.002558154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01149303,"about_ca_topic_score_gemma":0.02007163,"domain_scores_codex":[0.9982821,0.0002423165,0.0004869882,0.000463495,0.0003493593,0.0001757976],"domain_scores_gemma":[0.9960614,0.001338899,0.0007319975,0.0007471068,0.0009156045,0.0002049566],"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":[0.0003240981,0.00003190793,0.004953159,0.005438199,0.0001456483,0.00006478365,0.00004530769,0.0002091017,0.0003266609,0.0009969443,0.9674118,0.02005224],"study_design_scores_gemma":[0.00026404,0.00003781908,0.014504,0.00239929,0.0001590349,0.0002319715,0.00008303572,0.0001975689,0.0003244439,0.001572267,0.9801821,0.00004454401],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003436927,0.0009040284,0.0001817248,0.0001770534,0.00007704361,0.00005202865,0.9955726,0.0001715491,0.002520323],"genre_scores_gemma":[0.001489117,0.0009457514,0.0007929304,0.0003349026,0.00004067328,0.0003544113,0.9939287,0.0000642067,0.002049301],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09623908,"threshold_uncertainty_score":0.3219518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03177238327651868,"score_gpt":0.4436324610368365,"score_spread":0.4118600777603179,"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."}}