{"id":"W2520091533","doi":"10.1051/photon/20168219","title":"Détection et analyse automatique des aérosols atmosphériques par lidar ultraviolet ou infrarouge","year":2016,"lang":"fr","type":"article","venue":"Photoniques","topic":"Aeolian processes and effects","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Geography; Environmental science; Forestry; Art","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009556354,0.0004857547,0.0004882055,0.00007626461,0.000345296,0.0002844136,0.0003594524,0.0003851897,0.002456632],"category_scores_gemma":[0.0002682552,0.0003445283,0.0002185129,0.0004143875,0.000565209,0.001630322,0.00003661528,0.0003081186,0.0004609265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005689472,"about_ca_system_score_gemma":0.0002370737,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0105997,"about_ca_topic_score_gemma":0.00645158,"domain_scores_codex":[0.9972215,0.0004468203,0.0005230342,0.0006402548,0.0003269399,0.0008414625],"domain_scores_gemma":[0.9982475,0.0005138365,0.0002706227,0.0003900239,0.0001682273,0.0004097652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004331882,0.0004588851,0.5983433,0.002055095,0.0003539406,0.0002037266,0.007797732,0.0004801737,0.03748275,0.002502631,0.01263472,0.3372539],"study_design_scores_gemma":[0.0009864554,0.002078935,0.3292859,0.003219147,0.0002103343,0.0002805778,0.0003107549,0.008852476,0.4900294,0.02818338,0.1349968,0.001565853],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.952861,0.01304144,0.01781966,0.004197937,0.0007803318,0.0006194305,0.0003872549,0.0005771942,0.009715738],"genre_scores_gemma":[0.9624528,0.01574789,0.01421545,0.001095023,0.0003215576,0.00003270069,0.00006000948,0.00003018308,0.00604433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4525467,"threshold_uncertainty_score":0.9999007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01887910001766608,"score_gpt":0.2644980250083631,"score_spread":0.245618924990697,"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."}}