{"id":"W2097910870","doi":"10.1186/2046-4053-3-151","title":"Recovering the raw data behind a non-parametric survival curve","year":2014,"lang":"en","type":"review","venue":"Systematic Reviews","topic":"Probability and Statistical Research","field":"Mathematics","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre; Cancer Care Ontario; Public Health Ontario; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Raw data; Parametric statistics; Software; Raster graphics; Focus (optics); Process (computing); File format; Computer science; Raster data; Data file; Artificial intelligence; Data mining; Statistics; Database","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04782173,0.001464431,0.001101125,0.003752487,0.0006783421,0.003459159,0.002283333,0.001838038,0.01461869],"category_scores_gemma":[0.261819,0.0007938974,0.002535905,0.004389483,0.002955477,0.00304288,0.002263677,0.00365503,0.007759461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00129598,"about_ca_system_score_gemma":0.003025966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001711273,"about_ca_topic_score_gemma":0.001207058,"domain_scores_codex":[0.9754127,0.0121451,0.002531839,0.003053206,0.006360228,0.0004969058],"domain_scores_gemma":[0.7167345,0.1973055,0.02527475,0.04146641,0.0183238,0.0008950653],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001722565,0.0002328685,0.1036415,0.007588468,0.00152898,0.002154868,0.004478842,0.05740952,0.02057707,0.06661521,0.06158338,0.6724669],"study_design_scores_gemma":[0.0003436221,0.001543728,0.1539932,0.005818769,0.001445974,0.00781789,0.002949386,0.1598066,0.07421286,0.307941,0.2830785,0.001048462],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02955258,0.001102249,0.9485878,0.002169115,0.0006033996,0.000397342,0.008787857,0.005021133,0.003778626],"genre_scores_gemma":[0.3570335,0.002571391,0.6123244,0.001794192,0.0005026637,0.002132636,0.01467043,0.004216852,0.004754046],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9521782,"threshold_uncertainty_score":0.2529085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.575603463907282,"score_gpt":0.5300406054374976,"score_spread":0.04556285846978436,"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."}}