{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004218905,0.00008574477,0.0003165598,0.0000540284,0.0001072068,0.00002060049,0.00001662875,0.00007445024,0.000005586076],"category_scores_gemma":[0.0004140565,0.0001290043,0.0000835762,0.0001429655,0.00003319858,0.00005743726,0.00001884447,0.0001101489,0.000001267098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009491381,"about_ca_system_score_gemma":0.00002809899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003631886,"about_ca_topic_score_gemma":0.01419971,"domain_scores_codex":[0.9989575,0.00004904087,0.0003528012,0.0002314396,0.000174976,0.0002342733],"domain_scores_gemma":[0.9995214,0.00007347489,0.0001198081,0.0000875987,0.0001216822,0.00007608444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002850664,0.0003766633,0.4664662,0.00286009,0.0002727688,0.0001866233,0.0004150755,0.00001046556,0.3019775,0.00005091188,0.00232686,0.2247718],"study_design_scores_gemma":[0.008225055,0.0008209764,0.9448136,0.003883015,0.0001718607,0.00041538,0.001155948,0.002643279,0.01615983,0.009267273,0.01194441,0.0004993421],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953548,0.001706973,0.001302906,0.0001032568,0.0001745655,0.0004555649,0.000006514844,0.00002227623,0.0008731775],"genre_scores_gemma":[0.9902284,0.000432821,0.008788427,0.0001108836,0.00009179813,0.000003023795,0.000008703255,0.00002108257,0.0003149211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4783474,"threshold_uncertainty_score":0.7923772,"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."}}