{"id":"W2104494702","doi":"10.1007/s10546-004-9241-4","title":"The urban boundary-layer field campaign in marseille (ubl/clu-escompte): set-up and first results","year":2004,"lang":"en","type":"article","venue":"Boundary-Layer Meteorology","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":168,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Centre Scientifique et Technique du Bâtiment; Centre National de la Recherche Scientifique; Canadian Foundation for Climate and Atmospheric Sciences; National Oceanic and Atmospheric Administration; National Science Foundation","keywords":"Urban climatology; Planetary boundary layer; Environmental science; Meteorology; Boundary layer; Urban heat island; Urban climate; Geography; Urban planning; Aerospace engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001162641,0.0003860523,0.0003990796,0.0001109961,0.001061232,0.0002324698,0.0005224555,0.0003474295,0.0005160894],"category_scores_gemma":[0.0003579742,0.0003070272,0.00009797578,0.0003946076,0.0009441611,0.0003984787,0.0003991117,0.0005742587,0.000469009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004209043,"about_ca_system_score_gemma":0.000129947,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003910452,"about_ca_topic_score_gemma":0.02323267,"domain_scores_codex":[0.9968166,0.0002724276,0.0006942907,0.0008510543,0.0004245327,0.0009410345],"domain_scores_gemma":[0.9981653,0.0006645889,0.000177459,0.000753409,0.00002119985,0.0002180329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.005502364,0.0006857027,0.5601906,0.0001181258,0.0003414455,0.0006441487,0.04364185,0.0036809,0.01494582,0.009987964,0.3276952,0.03256587],"study_design_scores_gemma":[0.006328535,0.001139802,0.1661535,0.0000452795,0.00006509745,0.000236998,0.0005447241,0.0004621516,0.003919557,0.0222455,0.7980265,0.0008323432],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9758576,0.0009449722,0.0003728965,0.009420824,0.0009968114,0.0007074813,0.00003522847,0.00009570865,0.01156851],"genre_scores_gemma":[0.9945149,0.0001709431,0.0005459374,0.00213962,0.000154643,0.00009169606,0.00003476654,0.00004214982,0.002305346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4703313,"threshold_uncertainty_score":0.9999382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01442457747184352,"score_gpt":0.2358121613852426,"score_spread":0.221387583913399,"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."}}