{"id":"W2186053246","doi":"","title":"Multivariate analysis of seasonal pulp quality variations in a TMP mill","year":2004,"lang":"en","type":"article","venue":"Pulp & paper Canada","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pulp (tooth); Multivariate statistics; Seasonality; Mill; Environmental science; Multivariate analysis; Pulp and paper industry; Chip; Mathematics; Statistics; Engineering; Mechanical engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.00009105388,0.0001194678,0.0002481182,0.0001014322,0.00003280366,0.00001063153,0.00008578125,0.000039497,0.0001738167],"category_scores_gemma":[0.00002653945,0.0001090891,0.00007003357,0.0005807509,0.0000118006,0.00008728408,0.00001175697,0.00007491941,0.000002478515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003358194,"about_ca_system_score_gemma":0.0002184572,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8645524,"about_ca_topic_score_gemma":0.9762,"domain_scores_codex":[0.999202,0.00002999868,0.000252291,0.0001251499,0.0001920326,0.00019857],"domain_scores_gemma":[0.9996492,0.00005018858,0.00002914756,0.0001749537,0.00003106786,0.00006541499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00007293991,0.0002732823,0.2717813,0.0001807677,0.006253813,0.00007675777,0.005013081,0.6894237,0.0144416,0.006227475,0.0006545772,0.005600733],"study_design_scores_gemma":[0.0009001667,0.00001549168,0.9840615,0.00002091731,0.0004407062,6.979558e-7,0.0001500339,0.00882875,0.001680801,0.0002703643,0.0033356,0.0002949967],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948485,0.0006885529,0.0002425432,0.000446673,0.0001453428,0.0001236123,0.0002085177,0.00004752278,0.00324877],"genre_scores_gemma":[0.9991756,0.00001649552,0.0005152823,0.0000776792,0.0000169679,0.00002210794,0.00006363969,0.0000119118,0.0001003069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7122802,"threshold_uncertainty_score":0.4448526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01298589547349314,"score_gpt":0.2197342005628546,"score_spread":0.2067483050893615,"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."}}