{"id":"W2990272075","doi":"","title":"Enhancement of greenhouse gases associated with Canadian forest fire using multi sensor data","year":2008,"lang":"en","type":"article","venue":"37th COSPAR Scientific Assembly","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Greenhouse gas; Environmental science; Greenhouse effect; Atmospheric sciences; Meteorology; Remote sensing; Climate change; Global warming; Geography; Geology","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":[0.0004053983,0.0002479039,0.0002657101,0.0000207207,0.0006893658,0.00004583152,0.00076585,0.00008873389,0.0004101412],"category_scores_gemma":[0.00006682172,0.0002194757,0.00004378588,0.0005600617,0.001012955,0.0004312074,0.0004041427,0.0001244953,0.0001135152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006409364,"about_ca_system_score_gemma":0.0001448145,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07215341,"about_ca_topic_score_gemma":0.1665403,"domain_scores_codex":[0.9974624,0.00005679337,0.0003257947,0.0007586727,0.0007545357,0.0006418294],"domain_scores_gemma":[0.9982919,0.00003853668,0.0002352963,0.001053146,0.00001930763,0.0003617968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002004482,0.0004811715,0.9312624,0.000008300754,0.00006446217,0.0001201894,0.0004061101,0.05938713,0.005462881,0.000003046951,0.002000319,0.0007839506],"study_design_scores_gemma":[0.0007218132,0.0001373428,0.4091192,0.00007291161,0.00008509536,0.00003803481,0.0003107495,0.585669,0.001286791,0.000004192024,0.002037019,0.0005177268],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898778,0.00003802252,0.008894045,0.00003355273,0.0001786052,0.0003264507,0.00008673236,0.00003403258,0.0005308037],"genre_scores_gemma":[0.9664991,0.00001879978,0.02927935,0.0000695394,0.0000119869,0.000005662783,0.0001376589,0.00003423786,0.003943665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.526282,"threshold_uncertainty_score":0.9340252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04346671352611543,"score_gpt":0.2355316615469187,"score_spread":0.1920649480208033,"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."}}