{"id":"W2094604707","doi":"10.1081/ese-100103481","title":"ESTIMATION OF ATMOSPHERIC MIXING HEIGHTS USING DATA FROM AIRPORT METEOROLOGICAL STATIONS","year":2001,"lang":"en","type":"article","venue":"Journal of Environmental Science and Health Part A","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Beijing; Environmental science; Depth sounding; Meteorology; Atmospheric instability; Adiabatic process; Wind speed; Mixing (physics); Atmospheric model; Atmospheric sciences; Precipitation; Atmospheric sounding; Geology; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001426367,0.000065943,0.0001878907,0.00002632831,0.0003464398,0.0000242601,0.0002454815,0.00002553303,0.00115378],"category_scores_gemma":[0.00005683419,0.00004478869,0.00001954885,0.0001980212,0.0003311266,0.0006747159,0.00003342159,0.00009300424,0.000006404945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002154307,"about_ca_system_score_gemma":0.0001226598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002670848,"about_ca_topic_score_gemma":0.00007162763,"domain_scores_codex":[0.9986611,0.00005254332,0.0004642321,0.0001674879,0.0004599958,0.0001946146],"domain_scores_gemma":[0.9991472,0.00009941601,0.0003813636,0.0001370229,0.00001243206,0.0002225546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005822353,0.0001258315,0.7954457,0.000006864765,0.00001669496,0.00001481458,0.0003746856,0.09252009,0.000772613,0.00004125372,0.0001071675,0.110516],"study_design_scores_gemma":[0.0001496903,0.0002671615,0.7569079,0.000009652972,0.000011071,0.00001946827,0.0001382551,0.2404514,0.000006197387,0.001134736,0.0008606842,0.00004379638],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964709,0.0008095942,0.001937588,0.0003599284,0.0001052459,0.00007705241,0.00006207594,0.000002326158,0.0001752635],"genre_scores_gemma":[0.9804639,0.0004377663,0.01869531,0.0003134933,0.00005630727,7.511525e-8,0.00002715896,9.201086e-7,0.000005079722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1479313,"threshold_uncertainty_score":0.9997593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1278846434706963,"score_gpt":0.3277341981244041,"score_spread":0.1998495546537078,"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."}}