{"id":"W2975702197","doi":"","title":"APPLICATION OF SUPERABSORBENT COOLANT AS A NOVEL APPROACH TO SEMI-DRY MACHINING","year":2018,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"Engineering Technology and Methodologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; McMaster University","keywords":"Coolant; Machining; Superabsorbent polymer; Engineering; Manufacturing engineering; Environmental science; Materials science; Mechanical engineering; Composite material","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"],"consensus_categories":[],"category_scores_codex":[0.0001170341,0.0003103025,0.0003903064,0.0003470333,0.00005362111,0.00001142247,0.0005118767,0.000535724,0.0007942481],"category_scores_gemma":[0.00003357717,0.000364021,0.00009531601,0.000481311,0.00003648482,0.00008094269,0.00007372884,0.0003960984,0.00004510653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001090997,"about_ca_system_score_gemma":0.00002794802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007475949,"about_ca_topic_score_gemma":0.00006398619,"domain_scores_codex":[0.9990097,0.00002206037,0.0002092904,0.0003499261,0.000137891,0.0002711079],"domain_scores_gemma":[0.9993845,0.00004024486,0.00006832135,0.000361649,0.00007032164,0.00007494815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006007905,0.0002870193,0.0007366465,0.003660999,0.001093575,0.00002574526,0.006225108,0.09021679,0.1268294,0.02541673,0.001331742,0.7435755],"study_design_scores_gemma":[0.002425291,0.0005376947,0.005238552,0.00106936,0.000782209,0.00003331596,0.01777544,0.0865819,0.1357371,0.0005134211,0.74632,0.002985746],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04338287,0.000174875,0.4394289,0.000006654951,0.0004814067,0.0004592089,0.00004486473,0.0008933251,0.5151279],"genre_scores_gemma":[0.3926198,0.0002123168,0.3315343,0.00005472804,0.0002587472,0.00004281773,0.001090397,0.0003285807,0.2738583],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7449883,"threshold_uncertainty_score":0.9998811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01781254594921707,"score_gpt":0.2219692744826749,"score_spread":0.2041567285334578,"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."}}