{"id":"W7037850949","doi":"","title":"Evaporator Scaling at a Zero-effluent BCTMP Mill","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Effluent; Mill; Piping; Pulp mill; Boiler feedwater; Pulp (tooth); Scaling; Solubility; Work (physics)","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":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008674223,0.0009978925,0.001074632,0.0003448813,0.001887997,0.0002154456,0.001287265,0.0003177433,0.002144079],"category_scores_gemma":[0.000208021,0.00106508,0.0004255436,0.001209276,0.0001223618,0.0007775257,0.001486817,0.0008871107,0.0006054493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008848175,"about_ca_system_score_gemma":0.0006741512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001406207,"about_ca_topic_score_gemma":0.000363751,"domain_scores_codex":[0.993638,0.0004373624,0.001105415,0.002074613,0.001631437,0.001113128],"domain_scores_gemma":[0.9953488,0.0002347404,0.001282396,0.002267129,0.0003789296,0.0004880042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002118665,0.001614081,0.001328055,0.007768255,0.001411755,0.002385424,0.4933898,0.01783722,0.09003691,0.2280076,0.07081653,0.08328567],"study_design_scores_gemma":[0.0009588428,0.0003235504,0.0003631212,0.0007348384,0.0001171275,0.0001002689,0.01484792,0.01393677,0.007614295,0.0001855252,0.9588797,0.001938063],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.3494408,0.02839754,0.5836037,0.0009296002,0.02225874,0.003683337,0.0007090275,0.0008404554,0.01013686],"genre_scores_gemma":[0.2687637,0.003470577,0.1426746,0.002348853,0.002422916,0.002648192,0.01182706,0.0009531837,0.5648909],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8880631,"threshold_uncertainty_score":0.9994114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02352555013441746,"score_gpt":0.3435730075499767,"score_spread":0.3200474574155592,"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."}}