{"id":"W6904221168","doi":"10.1371/journal.pmed.1002935.g001","title":"Combined grant success rates by year across CIHR institutes.","year":2019,"lang":"en","type":"other","venue":"Figshare","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Public health; Health care; Work (physics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003280137,0.0007411456,0.000831007,0.01100268,0.0009673656,0.002023174,0.001896538,0.000452202,0.145761],"category_scores_gemma":[0.01633231,0.0005034457,0.0008639062,0.0172943,0.0003338092,0.001299276,0.001927954,0.00118934,0.04934859],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001783265,"about_ca_system_score_gemma":0.004316342,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2403286,"about_ca_topic_score_gemma":0.3656689,"domain_scores_codex":[0.99675,0.0003810594,0.0002968118,0.0004703668,0.001223836,0.0008779169],"domain_scores_gemma":[0.9879287,0.002368689,0.002048325,0.001156334,0.004641131,0.001856786],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001134071,0.0000178772,0.00913597,0.0002176942,0.00005167418,0.00001285144,0.00008085032,0.0001325874,0.00005892861,0.0008595838,0.9685345,0.02078407],"study_design_scores_gemma":[0.0001394253,0.00007569223,0.3204346,0.0004452982,0.0001681022,0.0001514514,0.0009760511,0.0005775947,0.000400904,0.0008958859,0.6756334,0.0001015492],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.01016616,0.001235295,0.0006008514,0.0009656033,0.0003768033,0.00010084,0.9295717,0.00228157,0.05470104],"genre_scores_gemma":[0.08986246,0.001858446,0.002402368,0.0006062227,0.0002078921,0.0005100466,0.7759004,0.002092762,0.1265593],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9982167,"threshold_uncertainty_score":0.4876192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0371198733896996,"score_gpt":0.3099887667202279,"score_spread":0.2728688933305283,"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."}}