{"id":"W2910206228","doi":"10.1080/09593330.2018.1564072","title":"How microwaves can help to study membrane ageing","year":2019,"lang":"en","type":"article","venue":"Environmental Technology","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Circulatory and Respiratory Health; Université Libanaise; CHIST-ERA; Université de Rennes 1; Agence Nationale de la Recherche","keywords":"Ageing; Membrane; Fouling; Service life; Materials science; Chemistry; Chemical engineering; Process engineering; Composite material; Engineering; Biochemistry; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001226173,0.000305619,0.0003074091,0.0002389407,0.0001465612,0.00004766772,0.0008416264,0.0002314306,0.003199895],"category_scores_gemma":[0.00003928669,0.0003010593,0.00005507908,0.0005110269,0.0003127637,0.0001832232,0.001192468,0.0003149769,0.005113095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003020093,"about_ca_system_score_gemma":0.000003343383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004127617,"about_ca_topic_score_gemma":0.00008945752,"domain_scores_codex":[0.9979817,0.00004506246,0.0002475625,0.0008208042,0.0003718045,0.0005330198],"domain_scores_gemma":[0.9987793,0.00002448486,0.0001020003,0.0009994636,0.000001154172,0.00009359654],"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":[0.00001123768,0.0002361411,0.1211729,0.000002760895,0.00002085065,0.00004829363,0.0003064777,0.000097404,0.8595185,0.00006853904,0.0001958445,0.01832115],"study_design_scores_gemma":[0.0008143405,0.0008282153,0.05968923,0.000006166921,0.00001777874,0.00004629786,0.00782465,0.00003161488,0.9126485,0.0005626811,0.01700401,0.0005265103],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913641,0.00003485632,0.00008627711,0.004737406,0.0001422614,0.001314766,0.00001019394,0.0005506101,0.001759567],"genre_scores_gemma":[0.9917297,0.00001687903,0.002258338,0.0003035859,0.00001287121,0.0001158892,0.000007226947,0.00004112398,0.005514375],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06148362,"threshold_uncertainty_score":0.9999442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007166521016557148,"score_gpt":0.2101070223706325,"score_spread":0.2029405013540753,"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."}}