{"id":"W2082809983","doi":"10.1016/j.scitotenv.2008.04.056","title":"A simulation-aided factorial analysis approach for characterizing interactive effects of system factors on composting processes","year":2008,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Composting and Vermicomposting Techniques","field":"Agricultural and Biological Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Factorial experiment; Process (computing); Environmental science; Water content; Main effect; Factorial analysis; Moisture; Interaction; Waste management; Process engineering; Mathematics; Chemistry; Computer science; Engineering; Statistics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003193271,0.0001214996,0.0002253019,0.00002716761,0.0005557944,0.00001701898,0.000526698,0.00002696129,0.000001942542],"category_scores_gemma":[0.0003341576,0.00003744792,0.0001529743,0.0005082954,0.0003797478,0.00008453202,0.0001829757,0.00007672143,3.194612e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000722774,"about_ca_system_score_gemma":0.00001162549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009714616,"about_ca_topic_score_gemma":3.059815e-7,"domain_scores_codex":[0.9988967,0.0000688143,0.0002343346,0.0002382269,0.000389123,0.0001727971],"domain_scores_gemma":[0.997792,0.001632534,0.0003697732,0.0001302025,0.00004356087,0.00003191579],"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":[0.00006600335,0.0001380509,0.001590012,0.00006368403,0.00005281842,1.108461e-7,0.0009302589,0.06733185,0.9294695,0.00002333582,8.736076e-7,0.0003334965],"study_design_scores_gemma":[0.0001316236,0.0004759896,0.2216386,0.0001570202,0.000146772,0.000002498419,0.0003810344,0.06585141,0.7110215,0.00002344001,0.000004633623,0.0001654134],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990304,0.000006961859,0.0002321835,0.00003349032,0.00009297093,0.0004874659,0.00002249624,0.0000337919,0.00006026685],"genre_scores_gemma":[0.9995779,0.000001056973,0.0003264442,0.000003070429,0.00005340104,0.00001456197,0.000007801244,0.000001019517,0.0000147674],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2200486,"threshold_uncertainty_score":0.4274777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02583738396774574,"score_gpt":0.2295748099849654,"score_spread":0.2037374260172197,"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."}}