{"id":"W7107945094","doi":"10.25545/cigyqw/bsqlqc","title":"MRI Bentheimer_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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007781787,0.003642401,0.001799328,0.003307205,0.001192892,0.003392983,0.002490198,0.001854935,0.2966917],"category_scores_gemma":[0.003293998,0.001477741,0.001352929,0.003738029,0.0004585373,0.002494205,0.002470948,0.001821188,0.4023958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008280255,"about_ca_system_score_gemma":0.001299903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005676856,"about_ca_topic_score_gemma":0.0106446,"domain_scores_codex":[0.9993512,0.00005146809,0.00005203457,0.0002698163,0.0001491924,0.0001263093],"domain_scores_gemma":[0.9983988,0.0003995294,0.0001568924,0.0005439349,0.0003967818,0.0001040077],"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":[0.0001091974,0.00003054548,0.0007434674,0.000646635,0.00002971704,0.00001818849,0.00002470591,0.0003111283,0.0006788329,0.0003819375,0.9877211,0.009304522],"study_design_scores_gemma":[0.0002010701,0.00003548394,0.005204693,0.0002888277,0.00004526085,0.0001009885,0.00006358926,0.0009043094,0.004358408,0.003252726,0.9854537,0.00009083766],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002579504,0.00008553998,0.000590097,0.00004672177,0.00006085398,0.00001588686,0.9886003,0.008437072,0.001905608],"genre_scores_gemma":[0.001816655,0.0001248206,0.002718465,0.00009947062,0.00003871534,0.0001302969,0.9860736,0.005252241,0.003745721],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7033082,"threshold_uncertainty_score":0.9925328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01147741258648349,"score_gpt":0.2683449593384271,"score_spread":0.2568675467519436,"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."}}