{"id":"W2043095730","doi":"10.1016/j.minpro.2010.02.001","title":"Tracking velocity of multiple bubbles in a swarm","year":2010,"lang":"en","type":"article","venue":"International Journal of Mineral Processing","topic":"Minerals Flotation and Separation Techniques","field":"Environmental Science","cited_by":53,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Bubble; Tracking (education); Trajectory; Particle tracking velocimetry; Software; Computer vision; Computer science; Artificial intelligence; Swarm behaviour; Pixel; Acoustics; Mechanics; Physics; Particle image velocimetry","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0003712149,0.00006524093,0.0001158791,0.0001218954,0.00001966592,0.00003515791,0.0002669789,0.00004242405,0.0003226288],"category_scores_gemma":[0.0002448621,0.00005582273,0.00004880167,0.0001098236,0.00007112086,0.0005090201,0.00003581484,0.0001999579,0.000004038952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004336488,"about_ca_system_score_gemma":0.00002877412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001092325,"about_ca_topic_score_gemma":0.0004236634,"domain_scores_codex":[0.9989679,0.00001942644,0.0004622737,0.00007823863,0.0003946221,0.00007746674],"domain_scores_gemma":[0.9993855,0.00003937274,0.0003700925,0.00003978864,0.000127431,0.00003786113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006703947,0.0001427956,0.0699058,0.000006711214,0.000006750375,0.00001678232,0.00107783,0.001228281,0.8289675,0.00007713502,0.0005798587,0.09792355],"study_design_scores_gemma":[0.002610103,0.0001618321,0.3193524,0.0002893938,0.00001498922,0.0003079942,0.0003804142,0.06535166,0.5941921,0.004625935,0.01232592,0.0003872451],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941792,0.00002125663,0.003142389,0.0004317193,0.0001944198,0.00003494458,0.000001471147,0.000007399664,0.001987219],"genre_scores_gemma":[0.9814174,0.00000695658,0.0182385,0.0001218482,0.00009978189,0.000001226015,0.000001513463,0.000005289738,0.0001074544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2494466,"threshold_uncertainty_score":0.353256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01749797636572143,"score_gpt":0.3019030510262255,"score_spread":0.2844050746605041,"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."}}