{"id":"W6907127637","doi":"10.20383/103.01071","title":"Bare Earth Digital Elevation Model, Snow Depth Models, and Snow Density Canopy Fractional Coverage raster data for the West Castle Watershed in the Oldman River headwaters of Alberta, Canada","year":2024,"lang":"en","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digital elevation model; Snow; Elevation (ballistics); Watershed; Lidar; Raster graphics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004951502,0.001225631,0.000711627,0.003871996,0.001494704,0.001471701,0.002318942,0.0007374707,0.020392],"category_scores_gemma":[0.001890815,0.0006861145,0.0006431423,0.01011023,0.0004593506,0.000514767,0.0007774427,0.0008917073,0.01183115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01192721,"about_ca_system_score_gemma":0.02163991,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9745237,"about_ca_topic_score_gemma":0.9882895,"domain_scores_codex":[0.9994449,0.00002090384,0.00002593939,0.00008731897,0.000281828,0.0001391603],"domain_scores_gemma":[0.9984108,0.00009820791,0.00007665351,0.000127404,0.001117582,0.0001693418],"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":[0.00006112522,0.0000407529,0.008552068,0.0003482054,0.00005236815,0.00006995114,0.0001604665,0.002097316,0.0002508269,0.001331189,0.9801003,0.006935418],"study_design_scores_gemma":[0.0001317406,0.000007981292,0.06533682,0.0003102625,0.00004477469,0.00005815805,0.0005821862,0.002842647,0.0007549787,0.000905776,0.9289529,0.00007178486],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00106222,0.0000417529,0.00009203022,0.00003158511,0.000008046728,0.00001301892,0.9971818,0.0001637157,0.00140589],"genre_scores_gemma":[0.001817276,0.00004857285,0.0004522582,0.00001150942,0.000001906376,0.00002605554,0.9961533,0.00003642201,0.001452735],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02547634,"threshold_uncertainty_score":0.08653831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06229727543710903,"score_gpt":0.2932843630384848,"score_spread":0.2309870876013758,"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."}}