{"id":"W6926068389","doi":"10.21227/rdk9-cr98","title":"Alberta River Ice Segmentation Dataset","year":2019,"lang":"en","type":"dataset","venue":"IEEE DataPort","topic":"Personality Traits and Psychology","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Bridge (graph theory); Aerial photos; High resolution; Segmentation; Aerial survey; Digital camera; Video camera","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004821614,0.003329921,0.001433248,0.004176403,0.001566423,0.00191336,0.003111056,0.001742107,0.01317216],"category_scores_gemma":[0.001221515,0.0004828856,0.001255161,0.005602862,0.0005980278,0.0007717689,0.00128341,0.001501499,0.02491497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002756752,"about_ca_system_score_gemma":0.003582258,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3175886,"about_ca_topic_score_gemma":0.626895,"domain_scores_codex":[0.9992065,0.00005412515,0.00003497216,0.0002413342,0.0002755734,0.0001874216],"domain_scores_gemma":[0.9994316,0.00004923952,0.00002671656,0.0001124281,0.000304758,0.00007535245],"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":[0.0001653181,0.0001060902,0.002991578,0.0005463957,0.00008754166,0.0002120373,0.00006964974,0.001301088,0.001182573,0.0004775839,0.9747611,0.01809906],"study_design_scores_gemma":[0.0001704821,0.00004531677,0.02573189,0.0003318378,0.00009421734,0.0004000117,0.0004318886,0.0057049,0.002417765,0.001062006,0.9635108,0.00009896876],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005248328,0.001035516,0.0007212599,0.0001541643,0.0001467889,0.00009891942,0.9823168,0.003293197,0.006985102],"genre_scores_gemma":[0.001913917,0.0001288686,0.0009921069,0.00003804368,0.00001027813,0.00004148332,0.9954313,0.00007732215,0.001366632],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6824114,"threshold_uncertainty_score":0.6314801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0734942866629488,"score_gpt":0.3940553859022658,"score_spread":0.320561099239317,"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."}}