{"id":"W6969410134","doi":"10.5683/sp3/wwnjbh","title":"NPC bidirectional crowding dataset","year":2023,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Code (set theory); Scale (ratio); Cooperativity; Nanoscopic scale; Clogging","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":[0.0008937853,0.002357516,0.00178693,0.001784337,0.001473755,0.00162805,0.004142013,0.003582777,0.08324395],"category_scores_gemma":[0.004705444,0.0009247622,0.002097761,0.003205773,0.0006138798,0.0008178065,0.001357171,0.002686446,0.05582291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001672653,"about_ca_system_score_gemma":0.002969615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04460285,"about_ca_topic_score_gemma":0.08537363,"domain_scores_codex":[0.999316,0.0001181577,0.00003872815,0.0001713206,0.0002352244,0.000120606],"domain_scores_gemma":[0.9983584,0.0007955048,0.00007658913,0.0003065541,0.0003105968,0.0001522704],"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":[0.00009936692,0.00009775764,0.0009087672,0.0008686875,0.00008894528,0.00005073162,0.00004399224,0.01467059,0.0004865995,0.002035044,0.9776969,0.002952618],"study_design_scores_gemma":[0.001411427,0.00008381489,0.00426523,0.0003769888,0.0001457276,0.0001367105,0.0001480448,0.05416054,0.003584424,0.01544286,0.9200852,0.0001589955],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00125682,0.0001067804,0.0004488686,0.0001655989,0.00006036418,0.00003343076,0.9936469,0.001702556,0.002578774],"genre_scores_gemma":[0.003191553,0.00008774234,0.001482459,0.0001288386,0.00001230039,0.0002081403,0.9930875,0.0005076527,0.001293877],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08324395,"threshold_uncertainty_score":0.2784787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04922842137891442,"score_gpt":0.3249898647859537,"score_spread":0.2757614434070392,"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."}}