{"id":"W4249451416","doi":"10.1016/s1365-6937(20)30182-9","title":"Alfa Laval partners with Orège","year":2020,"lang":"en","type":"article","venue":"Filtration Industry Analyst","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Psychology","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":["research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.00004627116,0.0000909314,0.0001556845,0.00004521419,0.0000730235,0.00000981616,0.00005174896,0.0025336,0.0008123147],"category_scores_gemma":[0.00004401829,0.00006575468,0.00004041818,0.0004425235,0.00008745773,0.00006078416,0.000008591176,0.002791759,0.00009295346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009973625,"about_ca_system_score_gemma":0.00009488544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001028988,"about_ca_topic_score_gemma":0.000005856089,"domain_scores_codex":[0.9994054,0.00001859626,0.000147183,0.0001818641,0.0001228613,0.0001240566],"domain_scores_gemma":[0.9996202,0.00001075795,0.00005468831,0.0001416581,0.00004394675,0.0001287485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002022486,0.0005590432,0.4691264,0.0002405849,0.002750733,0.001501169,0.002161153,0.001858113,0.06306342,0.01912515,0.431066,0.006525814],"study_design_scores_gemma":[0.008582997,0.003929355,0.08697144,0.0004249484,0.00255924,0.001063492,0.005249292,0.01168254,0.286718,0.0001239708,0.5914232,0.001271632],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5465521,0.0001487602,0.002939587,0.4044762,0.0001028296,0.0003198159,0.00001279165,0.000433152,0.04501473],"genre_scores_gemma":[0.9936149,0.00002328977,0.0002647331,0.004284772,0.000185075,0.000005711401,0.00007151375,0.000007993619,0.00154203],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4470628,"threshold_uncertainty_score":0.9995089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03022340369494762,"score_gpt":0.2807036390118516,"score_spread":0.2504802353169039,"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."}}