{"id":"W6932056016","doi":"10.5683/sp3/ceyu10","title":"MountainScape Segmentation Dataset","year":2024,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Oblique case; Segmentation; RGB color model; Image segmentation; Grayscale; Classifier (UML); Pattern recognition (psychology); Land cover","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":[0.0007644814,0.003976387,0.001685097,0.00324404,0.001553411,0.002279937,0.003855004,0.002551631,0.02696069],"category_scores_gemma":[0.001897547,0.0006181166,0.002307727,0.003755883,0.0006101572,0.001504958,0.001815565,0.001949031,0.04253843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001491501,"about_ca_system_score_gemma":0.001564749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04320252,"about_ca_topic_score_gemma":0.1291991,"domain_scores_codex":[0.9988002,0.0001365146,0.00008289871,0.0004392811,0.0003708966,0.0001702182],"domain_scores_gemma":[0.9993975,0.00009667184,0.00003074759,0.0001784135,0.0002254979,0.00007118435],"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":[0.0001576549,0.0001669271,0.001792492,0.0007448076,0.0001296318,0.0001529091,0.00005801994,0.001870885,0.001191621,0.0005630285,0.9758749,0.01729705],"study_design_scores_gemma":[0.000300694,0.0001210279,0.01595172,0.0003091642,0.0001535442,0.0006675649,0.0003431434,0.01116204,0.00390922,0.001807839,0.9651402,0.0001339458],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005911313,0.001137514,0.001567876,0.0002469498,0.0002453746,0.0001518156,0.9746294,0.008470351,0.007639334],"genre_scores_gemma":[0.002330888,0.00009686001,0.001813216,0.00006079419,0.0000149991,0.00007343683,0.9941076,0.0001967325,0.001305477],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04320252,"threshold_uncertainty_score":0.09019256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02256671284698142,"score_gpt":0.3161299695538926,"score_spread":0.2935632567069112,"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."}}