{"id":"W4236695007","doi":"10.1515/iupac.83.0343","title":"Channel Blocker","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Glossary; Context (archaeology); Process (computing); Field (mathematics); Computer science; Multidisciplinary approach; Data science; Component (thermodynamics); Management science; Engineering; Sociology; Biology; Linguistics; Social science","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":[0.0008904562,0.001017474,0.001905458,0.001426755,0.0006598834,0.001840226,0.001965123,0.001627491,0.1012461],"category_scores_gemma":[0.006260791,0.0003623095,0.001562715,0.002209167,0.0003039151,0.001450575,0.001141006,0.002233482,0.08694141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009669224,"about_ca_system_score_gemma":0.001945101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005018576,"about_ca_topic_score_gemma":0.01263017,"domain_scores_codex":[0.9988865,0.0001332315,0.0002217293,0.0003939423,0.0002398819,0.0001246242],"domain_scores_gemma":[0.9973334,0.0008724954,0.0004922093,0.0005979909,0.000490461,0.0002134601],"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":[0.001372847,0.00009880228,0.004699445,0.003259667,0.0001274766,0.0001313115,0.00003099322,0.0003502559,0.0005364417,0.001087306,0.9628105,0.0254948],"study_design_scores_gemma":[0.001036604,0.0001559777,0.01500705,0.001419285,0.0002918777,0.0007266714,0.00007085916,0.0004191975,0.001092537,0.003275843,0.976442,0.00006200678],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001090582,0.001037267,0.000410881,0.0003429588,0.0001277017,0.00009033875,0.9895578,0.0006144441,0.006728016],"genre_scores_gemma":[0.003845149,0.001162288,0.0009822617,0.001036477,0.00007570255,0.0003120234,0.9872958,0.0001738604,0.005116411],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1012461,"threshold_uncertainty_score":0.3387018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01501928225197081,"score_gpt":0.3815599501842237,"score_spread":0.3665406679322529,"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."}}