{"id":"W6951115112","doi":"10.5683/sp2/remsz6","title":"McGill Multicancer Model Technical Documentation","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Documentation; Population; Information model; Work (physics); Data modeling","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002362963,0.0004293086,0.0004925579,0.0002028525,0.0001212319,0.00008434882,0.0005299291,0.0005256073,0.0004686457],"category_scores_gemma":[0.0002842868,0.0004345018,0.0001912204,0.0002927773,0.0001147352,0.0002095746,0.0002717726,0.0005398077,0.0005750054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007181831,"about_ca_system_score_gemma":0.0002128986,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05693842,"about_ca_topic_score_gemma":0.07226311,"domain_scores_codex":[0.9974291,0.0001104294,0.0004873922,0.0007435057,0.0008003027,0.0004293186],"domain_scores_gemma":[0.9977772,0.00007154063,0.0002815356,0.001476181,0.0002125027,0.0001810349],"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":[0.00003393661,0.0001299831,2.788902e-7,0.0000636661,0.00006016587,0.00006382439,0.000003111513,0.0006140104,0.0003224697,0.0000824564,0.9984314,0.0001946293],"study_design_scores_gemma":[0.0004585752,0.00001681159,0.00003653163,0.0001000401,0.0003057761,0.000018149,0.000008175818,0.001110331,0.0001407903,0.000190477,0.997135,0.0004793631],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[7.316454e-7,0.0001048473,0.00004324207,0.00009045529,0.00008494006,0.0003920001,0.9979236,0.0001941905,0.001166053],"genre_scores_gemma":[0.000004497135,0.0003466981,0.002431475,0.0005017681,0.0001827268,0.0003305725,0.995966,0.0001263594,0.0001099388],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01532469,"threshold_uncertainty_score":0.9998107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03105344786263242,"score_gpt":0.3351557495648616,"score_spread":0.3041023017022292,"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."}}