{"id":"W1970481717","doi":"10.1139/x03-014","title":"High-resolution forest fire weather index computations using satellite remote sensing","year":2003,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Relative humidity; Meteorology; Remote sensing; Satellite; Air temperature; Angstrom; Weather station; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.00055666,0.0005365157,0.0003525777,0.00123664,0.0004316015,0.0006053434,0.0004656618,0.0002290566,0.001085762],"category_scores_gemma":[0.002451721,0.0003071328,0.0003287811,0.001477628,0.0001376191,0.0004641232,0.0003121182,0.0002509187,0.0003090836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001264356,"about_ca_system_score_gemma":0.001586171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4680303,"about_ca_topic_score_gemma":0.6168779,"domain_scores_codex":[0.9997383,0.00003289211,0.00001935476,0.00004746186,0.0001211338,0.00004095508],"domain_scores_gemma":[0.9994956,0.0001141231,0.00004829024,0.00004977289,0.0002586742,0.00003352724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000419891,0.0002116094,0.2326638,0.0001447563,0.0002954622,0.0001743876,0.0002609967,0.5117912,0.03034863,0.001063078,0.003563866,0.2190625],"study_design_scores_gemma":[0.00005098663,0.00003043679,0.1828938,0.00000990102,0.00003581662,0.0000341658,0.0001139403,0.8092953,0.006144707,0.000360199,0.0009986196,0.00003207356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9374288,0.00009993199,0.05348403,0.00004201266,0.00001529929,0.0001145796,0.003943893,0.001522553,0.003348894],"genre_scores_gemma":[0.9236091,0.00007508358,0.07137792,0.00001219775,0.000009988951,0.00004789107,0.004161821,0.00007510133,0.0006307777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4680303,"threshold_uncertainty_score":0.9306122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03744747482098378,"score_gpt":0.2832266683651734,"score_spread":0.2457791935441896,"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."}}