{"id":"W2550770476","doi":"","title":"Water Soft-path Application in Industrial Systems: A Pulp and Paper Case Study","year":2007,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Material Properties and Processing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Waterloo","keywords":"Pulp (tooth); Engineering; Pulp and paper industry; Dentistry; Medicine","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0002194612,0.0001967057,0.0003255608,0.0002091364,0.00009684594,0.00004519238,0.0001097857,0.0003085548,0.00003747022],"category_scores_gemma":[0.000002306217,0.0001847233,0.00002875835,0.00008874615,0.00002083917,0.0002142893,0.00003079982,0.0002209563,0.000009230443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006412839,"about_ca_system_score_gemma":0.00001451782,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1036773,"about_ca_topic_score_gemma":0.05598031,"domain_scores_codex":[0.9992138,0.0000335055,0.0001670691,0.0002310365,0.000134324,0.0002203049],"domain_scores_gemma":[0.9996732,0.000007526676,0.00005800483,0.0001552483,0.00005016788,0.00005585078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.001061292,0.0002838049,0.00379674,0.006202688,0.0003376208,0.003228309,0.8916333,0.003867124,0.04562693,0.00001913217,0.00050606,0.04343702],"study_design_scores_gemma":[0.002186294,0.0002147311,0.000485926,0.0004877061,0.0002042804,0.0001121804,0.9833229,0.008657418,0.001931287,0.0000138085,0.001661525,0.0007219992],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986328,0.0002147362,0.00001944611,0.00001751985,0.0003227305,0.0005526622,0.000009672523,0.00006738319,0.0001630814],"genre_scores_gemma":[0.9849119,0.00003026602,0.00003214319,0.000001659876,0.00006840785,0.000002043796,0.000105986,0.00003056385,0.01481704],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09168956,"threshold_uncertainty_score":0.9612456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0135792265166369,"score_gpt":0.2006174198389576,"score_spread":0.1870381933223207,"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."}}