{"id":"W4398656049","doi":"10.7910/dvn/c6wcuy/tqr4jo","title":"MangerSattlerCPS_ReplicationCode.do","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001617932,0.003244078,0.002177245,0.005795373,0.001103567,0.00421905,0.004433715,0.002694091,0.2352358],"category_scores_gemma":[0.0116545,0.001274814,0.001476157,0.008155616,0.0007843486,0.002736162,0.003444043,0.001992845,0.2433445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001510806,"about_ca_system_score_gemma":0.003050804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0169984,"about_ca_topic_score_gemma":0.02380573,"domain_scores_codex":[0.9986389,0.0002307818,0.0001590414,0.0004981182,0.0002623463,0.0002107359],"domain_scores_gemma":[0.9961003,0.001337386,0.0003990165,0.001059573,0.0006749342,0.0004288022],"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":[0.00008013463,0.00001014616,0.0005365533,0.001107434,0.00004385508,0.00001677306,0.00002933707,0.0001827269,0.0001085913,0.0006503884,0.9951048,0.002129263],"study_design_scores_gemma":[0.0002220025,0.00001310054,0.001264126,0.0003876027,0.00003766318,0.00003231383,0.00004341832,0.0003255468,0.0003940484,0.002458602,0.9947829,0.00003869034],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004800707,0.00008038989,0.00007710566,0.00006549503,0.00001913825,0.000006094533,0.99793,0.001183701,0.0005899863],"genre_scores_gemma":[0.0005002539,0.0001215135,0.0003507231,0.00008190975,0.0000117837,0.00006598792,0.9974737,0.0006209972,0.000773113],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7647642,"threshold_uncertainty_score":0.7869421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01411686836498525,"score_gpt":0.2793997627261176,"score_spread":0.2652828943611323,"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."}}