{"id":"W6889076333","doi":"10.25545/bhmcou","title":"Crack Roboflow DTI UNB","year":2024,"lang":"en","type":"dataset","venue":"UNB Dataverse","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Department of Transportation, Infrastructure and Energy; Current Water Technologies (Canada); University of New Brunswick","funders":"","keywords":"Annotation; Segmentation; Image segmentation; Visualization; Resource (disambiguation); Pattern recognition (psychology)","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006884201,0.001134985,0.0009190439,0.001102742,0.0001677039,0.000519933,0.002669054,0.0008754046,0.05726784],"category_scores_gemma":[0.0005801874,0.001121071,0.0003538062,0.001231786,0.0003209799,0.0006331732,0.002259656,0.002044156,0.9758658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000579314,"about_ca_system_score_gemma":0.0005593451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001022122,"about_ca_topic_score_gemma":0.001601435,"domain_scores_codex":[0.9948353,0.000211308,0.0007652449,0.001851764,0.001240024,0.001096343],"domain_scores_gemma":[0.9934174,0.0001659006,0.0003481391,0.005461746,0.0001339313,0.0004728812],"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":[0.00006851666,0.0001801679,0.000001384242,0.0005604575,0.0003777238,0.002278958,0.00002317925,0.00003819959,0.00004580618,0.00004398002,0.9962349,0.0001467581],"study_design_scores_gemma":[0.000582771,0.00006930478,0.000003368933,0.0004836652,0.001143091,0.0001075216,0.00006145612,0.0000982442,0.00003788579,0.0001265152,0.9960876,0.001198543],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000006029444,0.00009715887,0.000003647119,0.00003550105,0.00384457,0.0006213281,0.9937558,0.0006127801,0.001023219],"genre_scores_gemma":[0.00000134128,0.0003623549,0.0003424587,0.0004649217,0.001535163,0.00005052629,0.9938466,0.0003831484,0.003013462],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9185979,"threshold_uncertainty_score":0.9991239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02265830510564791,"score_gpt":0.2838237375920988,"score_spread":0.2611654324864509,"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."}}