{"id":"W2745660863","doi":"","title":"Differential Absorption Lidar (DIAL) in Alberta: A New Remote Sensing Tool for Wide Area Measurement of Particulates, CO2, and CH4 Emissions from Energy Extraction and Production Sites","year":2014,"lang":"en","type":"article","venue":"","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Dial; Lidar; Remote sensing; Environmental science; Particulates; Extraction (chemistry); Production (economics); Absorption (acoustics); Meteorology; Geography; Engineering; Materials science; Chemistry; Electrical 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":[0.0002021755,0.0002395039,0.0001735647,0.0005410304,0.0009496676,0.0005832193,0.0005584653,0.0003654705,0.0009966043],"category_scores_gemma":[0.0001827541,0.0001592042,0.0001087288,0.0008752776,0.0003578823,0.0002957236,0.0005113315,0.0002903864,0.0002391454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003767905,"about_ca_system_score_gemma":0.006903891,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9007077,"about_ca_topic_score_gemma":0.9592071,"domain_scores_codex":[0.9998041,0.000008161924,0.000003192341,0.00003002248,0.0001142581,0.00004019973],"domain_scores_gemma":[0.9998536,0.000008237777,0.000009283657,0.000006041982,0.00009702638,0.00002582246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001528435,0.0003887923,0.4561594,0.0003157834,0.0001113249,0.001666671,0.001987521,0.01586298,0.2137079,0.002168765,0.01028323,0.2958192],"study_design_scores_gemma":[0.0001438864,0.0001435399,0.8982438,0.00004681318,0.00008266678,0.0003806293,0.002573452,0.04316904,0.02424376,0.000765608,0.03010731,0.00009956751],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9797285,0.0004432375,0.005715421,0.0004112775,0.00003051134,0.00006139104,0.002644697,0.0004266563,0.01053838],"genre_scores_gemma":[0.9813405,0.0002486341,0.01037071,0.00009246442,0.000008658352,0.00001817996,0.001012166,0.00002434363,0.006884472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09929228,"threshold_uncertainty_score":0.199754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01136808857236507,"score_gpt":0.1963866561283721,"score_spread":0.1850185675560071,"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."}}