{"id":"W3023434011","doi":"10.1021/ie000486s","title":"Flooding Capacity in Packed Towers:  Database, Correlations, and Analysis","year":2000,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dimensionless quantity; Standard deviation; Database; Generalization; Mathematics; Sphericity; Artificial neural network; Flooding (psychology); Reynolds number; Packed bed; Statistics; Computer science; Mechanics; Artificial intelligence; Geometry; Physics; Chemistry; Mathematical analysis; Chromatography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007035084,0.00009919198,0.0001480835,0.00007529049,0.0001089259,0.00006054527,0.0001397377,0.0001022722,0.002218693],"category_scores_gemma":[0.0001719816,0.0001023969,0.00002994007,0.001117679,0.000101901,0.0001711184,0.0001146159,0.0004680756,0.00004696047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001873656,"about_ca_system_score_gemma":0.000009205565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006221056,"about_ca_topic_score_gemma":0.00002365532,"domain_scores_codex":[0.9988064,0.00003545477,0.0001787592,0.0002804358,0.0003801605,0.0003187928],"domain_scores_gemma":[0.9995586,0.0001360684,0.00001292845,0.0001874586,0.0000118374,0.0000931031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006694249,0.0001536539,0.5283632,0.00003667944,0.0002616416,0.00005025979,0.00134562,0.02795722,0.3747316,0.0000281067,0.002059286,0.06494582],"study_design_scores_gemma":[0.006310341,0.0001135643,0.4116911,0.0002798768,0.0003233386,0.00002745893,0.001609972,0.1812401,0.2463488,0.00007015756,0.1501089,0.001876505],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979865,0.00003265325,0.0000650498,0.0001087188,0.00002211414,0.00009289617,0.00001623325,0.00002572579,0.001650126],"genre_scores_gemma":[0.9966458,0.00002714516,0.00003990777,0.000003223105,0.00007022176,0.00002549906,0.00003058813,0.000006651038,0.003150966],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1532828,"threshold_uncertainty_score":0.9986934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09956049106168594,"score_gpt":0.2918988392215664,"score_spread":0.1923383481598805,"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."}}