{"id":"W1995542117","doi":"10.1108/02644400710718574","title":"Computing orientation distribution and rheology of turbulent fiber suspensions flowing through a contraction","year":2007,"lang":"en","type":"article","venue":"Engineering Computations","topic":"Rheology and Fluid Dynamics Studies","field":"Chemical Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Rheology; Turbulence; Orientation (vector space); Materials science; Contraction (grammar); Mechanics; Classical mechanics; Physics; Mathematics; Geometry; Composite material; Medicine","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":[0.0001873168,0.0001203772,0.0001843764,0.0000635891,0.0001229385,0.000006545286,0.00004122353,0.00008797787,0.00001022882],"category_scores_gemma":[0.0001866642,0.0001330348,0.00004342919,0.0001967331,0.00005187025,0.0001070958,0.0000385585,0.0001795356,0.000005381315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005573038,"about_ca_system_score_gemma":0.00000820907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002630902,"about_ca_topic_score_gemma":0.000004686758,"domain_scores_codex":[0.9991982,0.00001113597,0.0003230343,0.0001669196,0.00008663699,0.00021407],"domain_scores_gemma":[0.9991819,0.0005505227,0.00004648605,0.00008202364,0.00009881717,0.00004023363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001518696,0.00004166101,0.001174312,0.00004606462,0.00009377737,0.000008225164,0.001054037,0.7919595,0.02158536,0.1831853,0.00004946678,0.0007870655],"study_design_scores_gemma":[0.0003578209,0.00002277015,0.0244026,0.00004480529,0.00003291245,0.000039156,0.0001003324,0.9728104,0.001904786,0.0000827757,0.000079117,0.0001225081],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3759696,0.0001126534,0.6234581,0.00006476818,0.0001633613,0.00006689205,0.00000370727,0.00008961142,0.00007131178],"genre_scores_gemma":[0.9756153,0.00001237352,0.02404737,0.00001328598,0.00006318495,0.000002629342,0.0001070726,0.00001290782,0.0001259199],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5996456,"threshold_uncertainty_score":0.5425003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007542306562436553,"score_gpt":0.2456337429438248,"score_spread":0.2380914363813883,"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."}}