{"id":"W7033948775","doi":"","title":"Snow-water-equivalent estimation using satellite data in forested and open areas in Ontario","year":2003,"lang":"en","type":"dissertation","venue":"The Atrium (University of Guelph)","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Snow; Brightness temperature; Satellite; Open water; Water equivalent; Snow cover; Special sensor microwave/imager","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":[0.0001642072,0.0001680601,0.0001927895,0.0005737965,0.0008618786,0.0005342998,0.0002567652,0.0001138725,0.0007518718],"category_scores_gemma":[0.0007710121,0.0001383779,0.0001848513,0.001501065,0.0003087037,0.0002105572,0.0002785914,0.00009772099,0.0001190125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009643539,"about_ca_system_score_gemma":0.006183102,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9870738,"about_ca_topic_score_gemma":0.9955974,"domain_scores_codex":[0.9998455,0.00001010508,0.000008833173,0.00002697841,0.00006130688,0.00004736209],"domain_scores_gemma":[0.9996825,0.00003489945,0.00004789891,0.000013939,0.0001725961,0.00004812501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000365741,0.00004832552,0.9345348,0.0001297208,0.00008970703,0.0004129834,0.00286648,0.008392868,0.008902021,0.0003751515,0.001579054,0.04230307],"study_design_scores_gemma":[0.00001244684,0.00001513399,0.9900053,0.00001093096,0.00002020519,0.00003045354,0.001099067,0.006387456,0.0006085339,0.00004997938,0.001750772,0.000009615002],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972146,0.00009084496,0.0001788397,0.0000314112,0.000001348634,0.00001235069,0.0008662165,0.00001047202,0.001594019],"genre_scores_gemma":[0.9966287,0.0001539866,0.0005919897,0.000006914154,0.000001524419,0.000007143654,0.001318578,0.00000498597,0.001286216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01292622,"threshold_uncertainty_score":0.06996912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03565940602585905,"score_gpt":0.2452571289574192,"score_spread":0.2095977229315602,"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."}}