{"id":"W4407296790","doi":"10.3390/data10020024","title":"Visual Footprint of Separation Through Membrane Distillation on YouTube","year":2025,"lang":"en","type":"article","venue":"Data","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Footprint; Separation (statistics); Distillation; Chromatography; Computer science; Process engineering; Environmental science; Chemistry; Engineering; Geography; Machine learning; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001485148,0.00007526625,0.00009852488,0.00002947263,0.00005124692,0.00001409173,0.0004360527,0.00005668271,0.0003424466],"category_scores_gemma":[0.0001786291,0.00006683914,0.000014091,0.0002491408,0.0001058655,0.0002182376,0.0004658473,0.00006062573,0.0001918472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004385207,"about_ca_system_score_gemma":0.000008338999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001474944,"about_ca_topic_score_gemma":0.0000914725,"domain_scores_codex":[0.9992092,0.00002611225,0.0001965152,0.0002850431,0.0001924563,0.00009073131],"domain_scores_gemma":[0.9990689,0.00004922884,0.00007377824,0.0007920265,0.000005634625,0.00001039178],"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":[0.000427062,0.0008939925,0.03676224,0.0001936294,0.0001256492,0.000005818754,0.001116663,0.0245021,0.5686727,0.09909041,0.07079814,0.1974116],"study_design_scores_gemma":[0.0006681813,0.0001872484,0.06348823,0.000056025,0.00004201913,0.000001272402,0.0002621348,0.03262178,0.7802404,0.005666257,0.1164682,0.0002982689],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8835781,0.00002586058,0.01693433,0.001189623,0.0002419766,0.000434245,0.0001800225,0.0001970667,0.09721883],"genre_scores_gemma":[0.997783,0.00002303083,0.001182168,0.0000904776,0.000008634687,0.000005268046,0.000446275,0.000003599734,0.0004575558],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2115677,"threshold_uncertainty_score":0.374955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04202778023521123,"score_gpt":0.3574743070452022,"score_spread":0.315446526809991,"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."}}