{"id":"W1869963300","doi":"10.1111/brv.12185","title":"The evolution of peer review as a basis for scientific publication: directional selection towards a robust discipline?","year":2015,"lang":"en","type":"review","venue":"Biological reviews/Biological reviews of the Cambridge Philosophical Society","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Rigour; Context (archaeology); Process (computing); Peer review; Engineering ethics; Quality (philosophy); Preprint; Scientific literature; Technical peer review; Computer science; Publishing; Scientific progress; Selection (genetic algorithm); Management science; Data science; Risk analysis (engineering); Political science; Engineering; Business; Epistemology; Law; World Wide Web","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","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.1188271,0.000528591,0.001513586,0.005022522,0.001747466,0.01126739,0.003864802,0.004394528,0.0009171474],"category_scores_gemma":[0.2228597,0.0005664814,0.0009409075,0.006541765,0.0117321,0.0106644,0.003656685,0.006869683,0.001470398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007102247,"about_ca_system_score_gemma":0.01917966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002922955,"about_ca_topic_score_gemma":0.003468046,"domain_scores_codex":[0.852139,0.0902705,0.01076547,0.006357756,0.03829588,0.002171418],"domain_scores_gemma":[0.7821785,0.0957917,0.02659808,0.02131804,0.06829869,0.005814957],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001258859,0.00004917247,0.00303161,0.01153789,0.0003271545,0.0002020465,0.002189406,0.0007499962,0.001507358,0.2481396,0.0388305,0.6933095],"study_design_scores_gemma":[0.00009432247,0.0001876261,0.008252377,0.01448648,0.0004119108,0.0008593758,0.001347542,0.00132506,0.002000033,0.131907,0.838956,0.0001722946],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.005495246,0.7404705,0.02733906,0.1957958,0.01415365,0.0002382019,0.00007886763,0.0002108633,0.01621771],"genre_scores_gemma":[0.1858116,0.709664,0.05123957,0.03003048,0.01549796,0.0005576293,0.0001467994,0.0002210315,0.006830996],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9949775,"threshold_uncertainty_score":0.6284253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8049729065057509,"score_gpt":0.5806009134012404,"score_spread":0.2243719931045105,"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."}}