{"id":"W6943983436","doi":"10.17605/osf.io/pt4vk","title":"Preregistrations","year":2018,"lang":"en","type":"other","venue":"Open Science Framework","topic":"Legal Cases and Commentary","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002226071,0.000124815,0.0001993625,0.0001123388,0.0001542955,0.0003081718,0.00117391,0.0001306806,0.03166345],"category_scores_gemma":[0.0001608366,0.00008334096,0.00004081908,0.000539594,0.0006477052,0.0001158661,0.0004976589,0.0002052995,0.0018385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005937814,"about_ca_system_score_gemma":0.0005231666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005844301,"about_ca_topic_score_gemma":0.0000702185,"domain_scores_codex":[0.9988506,0.000008907326,0.0001065475,0.0004101393,0.000396235,0.0002275442],"domain_scores_gemma":[0.9986436,0.00001877938,0.00008691755,0.001023834,0.00004186042,0.000184976],"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":[0.000008447624,0.0000524853,0.0003513101,0.00001183522,0.000009935272,0.00001770689,0.00003030429,1.947114e-8,0.00003282696,0.00620474,0.9907757,0.002504661],"study_design_scores_gemma":[0.000108894,0.000131076,0.0003189964,0.0006577797,0.00003379388,0.00003053604,0.00003281806,0.000005083999,0.00005999443,0.000722855,0.997776,0.0001221437],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0000539381,0.00009339167,0.0006063638,0.003520711,0.000613734,0.0006204314,0.00001401524,0.00005536059,0.9944221],"genre_scores_gemma":[0.001488792,0.00003141513,0.0398767,0.003451506,0.0008699857,0.00003357834,0.00001611162,0.00009924744,0.9541327],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.04028939,"threshold_uncertainty_score":0.9989387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03771958724123969,"score_gpt":0.3925910221622445,"score_spread":0.3548714349210048,"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."}}