{"id":"W2931015251","doi":"10.1088/1755-1315/240/6/062051","title":"Characterization of bubble cloud quality and evolution using optical probes","year":2019,"lang":"en","type":"article","venue":"IOP Conference Series Earth and Environmental Science","topic":"Fluid Dynamics and Mixing","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bubble; Mechanics; Hydroelectricity; Cloud computing; Work (physics); Mixing (physics); Flow (mathematics); Environmental science; Characterization (materials science); Meteorology; Physics; Computer science; Thermodynamics; Engineering; Optics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002773577,0.0001920258,0.0001126413,0.0005654276,0.0001889574,0.0004513431,0.0002680388,0.000321957,0.0009939262],"category_scores_gemma":[0.0004338146,0.000141312,0.0001383779,0.0003144305,0.0003034562,0.0004137653,0.0002784544,0.0004473656,0.0001820469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004106052,"about_ca_system_score_gemma":0.0001508934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002590977,"about_ca_topic_score_gemma":0.00231391,"domain_scores_codex":[0.9998117,0.00001122462,0.000005227887,0.00004349497,0.00008360042,0.00004476016],"domain_scores_gemma":[0.9995958,0.0001351326,0.0001232565,0.00002011204,0.00009432606,0.0000313167],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00009631224,0.00005190658,0.005677016,0.00004438637,0.000006361028,0.00005903945,0.00009066224,0.0005081369,0.9875584,0.0002915087,0.0001391339,0.005477236],"study_design_scores_gemma":[0.00001255562,0.0002271333,0.0273055,0.000006734515,0.00001867898,0.0001360419,0.0001308064,0.01642874,0.9543518,0.0001539386,0.001200422,0.00002775172],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9702664,0.0005393482,0.02574135,0.00006204855,0.00001767542,0.00006523036,0.0005301095,0.0002493187,0.002528502],"genre_scores_gemma":[0.9893571,0.0002756718,0.008981314,0.0000518534,0.00001155204,0.00004692756,0.0003176421,0.00004279952,0.000915239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002590977,"threshold_uncertainty_score":0.005151749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01114807044588128,"score_gpt":0.1983148747922322,"score_spread":0.1871668043463509,"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."}}