{"id":"W3127904453","doi":"10.1016/j.seppur.2021.118407","title":"Development of a self-sustained model to predict the performance of direct contact membrane distillation","year":2021,"lang":"en","type":"article","venue":"Separation and Purification Technology","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Membrane distillation; Porosity; Materials science; Mass transfer; Membrane; Permeation; Distillation; Thermodynamics; Flux (metallurgy); Efficient energy use; Concentration polarization; Energy balance; Process engineering; Chemistry; Chromatography; Composite material; Desalination; Engineering","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":[0.0002609007,0.0001027508,0.0001671017,0.0001123953,0.0001330138,0.00000977219,0.0001775227,0.0001281367,0.00007912252],"category_scores_gemma":[0.0001206878,0.00008352199,0.00001933843,0.0006857155,0.0001219031,0.000119405,0.00009933017,0.00007764115,0.00002052311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005847958,"about_ca_system_score_gemma":0.00006801449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002810077,"about_ca_topic_score_gemma":0.00003026898,"domain_scores_codex":[0.9989671,0.00003162815,0.0004214703,0.0002533659,0.0002040172,0.0001224888],"domain_scores_gemma":[0.9992735,0.00003414768,0.0002148707,0.0003728636,0.00007777773,0.00002678628],"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":[0.00005968469,0.0001343952,0.00879686,0.00007714974,0.00003496697,3.465792e-7,0.002723629,0.01047807,0.9335365,0.01775273,0.0003032931,0.02610236],"study_design_scores_gemma":[0.0002119596,0.00007079109,0.009354924,0.00001164469,0.00001472012,0.000004396082,0.0005449303,0.07354349,0.9099486,0.0002436669,0.005941234,0.0001096706],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885949,0.00005405833,0.006341249,0.001361974,0.00002449057,0.0003848552,0.000005533707,0.000158487,0.003074481],"genre_scores_gemma":[0.980409,0.00008112648,0.01900423,0.000039331,0.000003217893,0.00007672852,0.00002121774,0.00000626586,0.0003588494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06306542,"threshold_uncertainty_score":0.3405928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01271048435628138,"score_gpt":0.2510811672090304,"score_spread":0.238370682852749,"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."}}