{"id":"W1552526860","doi":"10.3334/ornldaac/386","title":"BOREAS TGB-05 Fire History of Manitoba 1980 to 1991 in Raster Format","year":2012,"lang":"en","type":"dataset","venue":"NASA Technical Reports Server (NASA)","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Forest Service","funders":"","keywords":"Raster graphics; Atmosphere (unit); Taiga; Trace gas; Environmental science; Biogeochemistry; Boreal; TRACE (psycholinguistics); Scale (ratio); Geography; Physical geography; Meteorology; Remote sensing; Forestry; Geology; Archaeology; Cartography; Oceanography; Computer science; Computer graphics (images)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004022361,0.001368975,0.0008873462,0.004506202,0.0008903159,0.0007812191,0.00230299,0.0005905204,0.009217152],"category_scores_gemma":[0.001525046,0.0006046633,0.0005482811,0.009509915,0.0003550972,0.000389434,0.0006799514,0.0008863249,0.007654525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004706967,"about_ca_system_score_gemma":0.009078785,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7418497,"about_ca_topic_score_gemma":0.8702243,"domain_scores_codex":[0.9997175,0.00001572525,0.00002886749,0.00007031677,0.0001027477,0.00006482172],"domain_scores_gemma":[0.9984114,0.00008396328,0.0001643978,0.0002346335,0.0008923225,0.000213318],"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":[0.0002703463,0.0001234754,0.03289967,0.0008251137,0.0001666653,0.0001854109,0.0002543319,0.002149891,0.001220282,0.0005893103,0.9540767,0.007238821],"study_design_scores_gemma":[0.0003790088,0.00004607555,0.3786101,0.0004565608,0.0001245575,0.000186986,0.001040918,0.001949802,0.002164098,0.0005121211,0.6144484,0.00008132427],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003432561,0.00003800774,0.00004247229,0.00003552651,0.00001345073,0.00002035126,0.9956762,0.0001614247,0.0005799773],"genre_scores_gemma":[0.003881329,0.00004324612,0.0002126206,0.00001515172,0.000003421955,0.00004955299,0.9949926,0.00002686096,0.0007751222],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2581503,"threshold_uncertainty_score":0.5193411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0251837294705577,"score_gpt":0.2515476213803319,"score_spread":0.2263638919097742,"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."}}