{"id":"W4394580812","doi":"10.3390/chemengineering8020042","title":"Application of Machine Learning Models in Coaxial Bioreactors: Classification and Torque Prediction","year":2024,"lang":"en","type":"article","venue":"ChemEngineering","topic":"Fluid Dynamics and Mixing","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Coaxial; Torque; Bioreactor; Artificial intelligence; Computer science; Machine learning; Engineering; Mechanical engineering; Physics; Chemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.00009054999,0.00008207909,0.00008394769,0.0001820833,0.000009230786,0.00001777784,0.00003143249,0.00005366735,0.000001549821],"category_scores_gemma":[0.00000571486,0.00009214872,0.00001562707,0.0002037825,0.000007735429,0.0001533419,0.00001064924,0.0001347721,7.467154e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006527919,"about_ca_system_score_gemma":0.000004348586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001607699,"about_ca_topic_score_gemma":0.000004367905,"domain_scores_codex":[0.9995701,0.000002400106,0.000165379,0.0001114227,0.00005624126,0.00009441222],"domain_scores_gemma":[0.9998758,0.00001820096,0.000008625628,0.00006470711,0.000009317841,0.000023393],"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":[0.0000012474,0.000004174857,0.0008236955,0.0003339074,0.00001237111,5.330661e-7,0.0002730303,0.5085036,0.47075,0.006474351,0.000004524871,0.01281851],"study_design_scores_gemma":[0.00007666604,0.000007023034,0.001539683,0.00007270477,0.000005137692,0.000001728965,0.00001808735,0.9931999,0.004091305,0.00009448034,0.0008207338,0.0000725176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5361121,0.002244441,0.4604743,0.000009885081,0.0001495416,0.0001085364,0.000010611,0.0003403412,0.0005502995],"genre_scores_gemma":[0.9988673,0.0003491052,0.0006157265,5.561486e-7,0.00004593013,0.00004005017,0.00004201432,0.00002661889,0.00001273091],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4846963,"threshold_uncertainty_score":0.3757716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00916722697445105,"score_gpt":0.1904505432799636,"score_spread":0.1812833163055126,"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."}}