{"id":"W7107960224","doi":"10.25545/cigyqw/o9snbr","title":"MRI Nugget_Parallel_profilescorrected.tab","year":2025,"lang":"","type":"dataset","venue":"UNB Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Position (finance); Curve fitting; Dispersion (optics); Raw data","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008836851,0.003610123,0.001832642,0.003152178,0.00134471,0.003325387,0.002705435,0.002038256,0.261208],"category_scores_gemma":[0.003357981,0.001639633,0.001364348,0.003379269,0.0004853031,0.002473875,0.002424543,0.001951921,0.349053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008925492,"about_ca_system_score_gemma":0.001313851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005295662,"about_ca_topic_score_gemma":0.009419853,"domain_scores_codex":[0.9993256,0.00005760323,0.0000573704,0.0002710548,0.0001602822,0.0001280912],"domain_scores_gemma":[0.9981853,0.0004305106,0.0001827328,0.0006388692,0.0004426124,0.000119855],"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":[0.0001699485,0.00003604739,0.0007814523,0.0007786786,0.00003598087,0.00002334154,0.00002947823,0.0003043488,0.001200368,0.0004290273,0.9862083,0.01000292],"study_design_scores_gemma":[0.0002344363,0.00004162528,0.005487866,0.0002849842,0.00005355394,0.0001310963,0.00005827135,0.0009586587,0.007702609,0.003313532,0.9816301,0.0001033205],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003624899,0.000111926,0.0009647525,0.00006899938,0.00008269463,0.00002457833,0.9836541,0.01222923,0.002501374],"genre_scores_gemma":[0.002246911,0.0001403823,0.00423645,0.0001334824,0.00004786673,0.0001782212,0.9808643,0.007601012,0.004551396],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.261208,"threshold_uncertainty_score":0.8738278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01127988457588134,"score_gpt":0.2738067838007003,"score_spread":0.2625268992248189,"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."}}