{"id":"W2346551530","doi":"","title":"Suomi NPP Satellite Continues to Monitor Alberta's Huge Wildfire","year":2016,"lang":"fi","type":"article","venue":"","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Satellite; Environmental science; Smoke; Meteorology; Daytime; Remote sensing; Climatology; Geography; Geology; Atmospheric sciences; Engineering","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":[0.0005703733,0.0004187807,0.0003164921,0.001259989,0.002529049,0.001050114,0.0006030952,0.0003164086,0.004025635],"category_scores_gemma":[0.0004091051,0.000134512,0.0001527123,0.001757887,0.0004244741,0.0003675146,0.0005368523,0.0005412997,0.0009488496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004672238,"about_ca_system_score_gemma":0.009411341,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9230128,"about_ca_topic_score_gemma":0.9833296,"domain_scores_codex":[0.9994306,0.0000113784,0.000004715132,0.00003816692,0.0004334568,0.00008165021],"domain_scores_gemma":[0.9991043,0.00002339294,0.00002389905,0.0000241178,0.0007042002,0.0001199375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005851491,0.0002714875,0.3474923,0.000207019,0.00009879662,0.0005682621,0.0008751697,0.004349484,0.03450591,0.002095454,0.1978838,0.4110672],"study_design_scores_gemma":[0.0001048312,0.000185531,0.6327819,0.0001441566,0.0001127045,0.0002485828,0.003546508,0.01169789,0.01368292,0.0009950019,0.3363982,0.0001018762],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6964224,0.002816693,0.008760742,0.00306575,0.0006437527,0.0003823327,0.02946887,0.005247362,0.2531921],"genre_scores_gemma":[0.8436236,0.002306052,0.02505305,0.0009742302,0.0001078276,0.0001057927,0.02369072,0.000394947,0.1037438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07698721,"threshold_uncertainty_score":0.1548812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00762529301620094,"score_gpt":0.2285707037343259,"score_spread":0.2209454107181249,"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."}}