{"id":"W2309918200","doi":"10.1007/3-540-26531-7_10","title":"The Comminution of Large Quantities of Wet Sediment for Analysis and Testing with Application to Dioxin-Contaminated Sediments from Lake Ontario","year":2005,"lang":"en","type":"book-chapter","venue":"Environmental Chemistry","topic":"Aquatic Invertebrate Ecology and Behavior","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Sediment; Bay; Environmental science; Comminution; Slurry; Hydrology (agriculture); Contamination; Geology; Environmental engineering; Oceanography; Geomorphology; Geotechnical engineering; Chemistry; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005329829,0.0004181618,0.0002190167,0.0008052276,0.001687555,0.0007945441,0.0006816939,0.0005540262,0.0044933],"category_scores_gemma":[0.0006509288,0.0003468888,0.0003563104,0.0009879072,0.0009170225,0.0004772061,0.0006817624,0.0007264377,0.001694518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004303869,"about_ca_system_score_gemma":0.004946718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3221256,"about_ca_topic_score_gemma":0.7526899,"domain_scores_codex":[0.9996056,0.0000218688,0.00002224711,0.00006103586,0.000251388,0.00003785267],"domain_scores_gemma":[0.9995371,0.0000980523,0.00003899113,0.0001079993,0.0001821595,0.00003573229],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001584548,0.00009877624,0.005402881,0.0006318202,0.0000245809,0.001579693,0.002202746,0.001230428,0.2989971,0.005318118,0.05780461,0.6265508],"study_design_scores_gemma":[0.00002386244,0.0002755185,0.03098124,0.0001007799,0.00004627894,0.001738879,0.0006444181,0.0008189061,0.1447581,0.0014728,0.819105,0.00003409233],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.318799,0.02322556,0.2043404,0.01120547,0.002264555,0.001807537,0.006053152,0.002874345,0.42943],"genre_scores_gemma":[0.2190994,0.01035759,0.1164969,0.002186272,0.0002428987,0.0003140137,0.003902569,0.0009356742,0.6464646],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3221256,"threshold_uncertainty_score":0.6405012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009031522943046724,"score_gpt":0.2024397229199468,"score_spread":0.1934081999769001,"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."}}