{"id":"W4283800923","doi":"10.5194/amt-2022-120-rc2","title":"Comment on amt-2022-120","year":2022,"lang":"en","type":"peer-review","venue":"","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Alberta Environment and Protected Areas; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Oceanic and Atmospheric Administration; Alberta Innovates; Jet Propulsion Laboratory; University of Alberta; National Aeronautics and Space Administration; California Institute of Technology; Environment and Climate Change Canada; Alberta Environment and Parks","keywords":"Extrapolation; Environmental science; Greenhouse gas; Range (aeronautics); Algorithm; Sampling (signal processing); Meteorology; Remote sensing; Statistics; Computer science; Mathematics; Geography; Engineering; Aerospace engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003238688,0.0008926415,0.0009661402,0.000777728,0.003057272,0.003927404,0.00329517,0.04951198,0.03579289],"category_scores_gemma":[0.01536481,0.0005119945,0.002028168,0.001036503,0.002182221,0.002586535,0.001765749,0.02769863,0.02969832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004805511,"about_ca_system_score_gemma":0.007439512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04487594,"about_ca_topic_score_gemma":0.0491364,"domain_scores_codex":[0.9974388,0.0002628753,0.0002167333,0.0003104721,0.001204711,0.0005663407],"domain_scores_gemma":[0.9962766,0.001215143,0.0002650041,0.0001948766,0.001360095,0.0006883387],"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":[0.00004970025,0.00002072914,0.0002434642,0.00005514717,0.000004340975,0.000261418,0.00005146579,0.00003050248,0.0002222537,0.002059876,0.9940333,0.002967727],"study_design_scores_gemma":[0.00002358131,0.00002640959,0.00134288,0.0001137346,0.00000888765,0.00008529406,0.0001003063,0.00010253,0.0001662617,0.001146559,0.9968569,0.00002673714],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0013099,0.002411572,0.0005237016,0.7778128,0.1408823,0.0002712843,0.003520003,0.0008251903,0.07244327],"genre_scores_gemma":[0.003213628,0.000591949,0.000345003,0.917304,0.02027166,0.0002261614,0.0005468423,0.000110187,0.0573905],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.04951198,"threshold_uncertainty_score":0.1197391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01343427155292484,"score_gpt":0.2404190288761637,"score_spread":0.2269847573232388,"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."}}