{"id":"W2075835179","doi":"10.1002/jsl.3000180206","title":"Delivering synthetic performance with VHVI speciality base fluids","year":2001,"lang":"en","type":"article","venue":"Journal of Synthetic Lubrication","topic":"Lubricants and Their Additives","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Petro-Canada","funders":"","keywords":"Viscosity index; Base (topology); Process engineering; Viscosity; Biochemical engineering; Automotive industry; Computer science; Base oil; Synthetic oil; Work (physics); Mechanical engineering; Materials science; Engineering; Mathematics; Composite material","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004344163,0.0004073267,0.0002320428,0.0003713302,0.0001888673,0.0005245656,0.000300214,0.0003708942,0.001025224],"category_scores_gemma":[0.0006024121,0.000104178,0.0001874802,0.0003028957,0.0001837057,0.0004251372,0.0003759527,0.0003681635,0.0004027666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002577876,"about_ca_system_score_gemma":0.0002180141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004684517,"about_ca_topic_score_gemma":0.0005519912,"domain_scores_codex":[0.9997172,0.00005262394,0.00002960088,0.00002791472,0.000126984,0.00004571541],"domain_scores_gemma":[0.9997593,0.00004379402,0.00005492268,0.00001702216,0.0000920827,0.00003285352],"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":[0.0001205763,0.00005316316,0.0001538725,0.0000842543,0.000008014688,0.0000313926,0.00003732755,0.000562208,0.9938783,0.0002214171,0.00008741883,0.004761942],"study_design_scores_gemma":[0.000003467272,0.000223369,0.0001067145,0.000002721712,0.00000397275,0.0000197359,0.00001066111,0.0007083709,0.9977132,0.00001709598,0.001188003,0.00000282128],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851243,0.001580835,0.009234584,0.00007391521,0.00005825912,0.00005104156,0.0001412412,0.0002516269,0.003484228],"genre_scores_gemma":[0.9920847,0.0006128916,0.005324075,0.00001971321,0.00001195523,0.00001555314,0.0001700361,0.00003605002,0.00172505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001025224,"threshold_uncertainty_score":0.003429711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009465760348391515,"score_gpt":0.1913649586939612,"score_spread":0.1818991983455697,"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."}}