{"id":"W3093828432","doi":"","title":"Satellite remote sensing for detection and inventory of mass wasting events in British Columbia","year":2003,"lang":"en","type":"article","venue":"EGS - AGU - EUG Joint Assembly","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Remote sensing; Satellite; Wasting; Geography; Computer science; Meteorology; Engineering; Medicine","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":[0.0003296476,0.0003314198,0.000291504,0.002246784,0.001653526,0.0008055526,0.001078437,0.0003481089,0.001563001],"category_scores_gemma":[0.001330635,0.000278712,0.0001381725,0.003940607,0.0003326125,0.0002475832,0.0006185236,0.0004094359,0.0002836493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009157721,"about_ca_system_score_gemma":0.009128371,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9928115,"about_ca_topic_score_gemma":0.9975271,"domain_scores_codex":[0.9997633,0.00003033437,0.00001599287,0.00004052396,0.00008242686,0.00006734713],"domain_scores_gemma":[0.9990006,0.0001191894,0.00009535656,0.00003661285,0.0006337519,0.00011442],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003164352,0.0001638547,0.9287791,0.000125426,0.0001002769,0.0004797389,0.002533755,0.003530267,0.004605377,0.0002951546,0.004921764,0.05414876],"study_design_scores_gemma":[0.00001251118,0.00001204841,0.9925804,0.00004128336,0.00002247423,0.0000336369,0.002117352,0.002435554,0.0004203691,0.00003630688,0.002275898,0.0000123968],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924443,0.0003667289,0.0001999313,0.0001224,0.000007216815,0.00006860523,0.002444319,0.00002185283,0.004324679],"genre_scores_gemma":[0.9921686,0.0004773826,0.0007640668,0.00005057656,0.000003452554,0.0000538755,0.001483003,0.000008934285,0.004990097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009157721,"threshold_uncertainty_score":0.06644422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02784413357222007,"score_gpt":0.2578325866749726,"score_spread":0.2299884531027525,"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."}}