{"id":"W1802674408","doi":"10.1007/s00267-015-0602-1","title":"Examining Screening-Level Multimedia Models Through a Comparison Framework for Landfill Management","year":2015,"lang":"en","type":"article","venue":"Environmental Management","topic":"Landfill Environmental Impact Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Fugacity; Advection; Environmental science; Benzene; Flux (metallurgy); Environmental remediation; Groundwater; Chemistry; Environmental engineering; Thermodynamics; Geology; Geotechnical engineering; Contamination; Physics; Physical chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004625618,0.0006204664,0.0005046789,0.00007240388,0.0003545379,0.00007807739,0.0006660505,0.0001427925,0.0008048062],"category_scores_gemma":[0.00001435737,0.0005805437,0.0001575645,0.0001849392,0.000404778,0.0006971707,0.002012791,0.0002287662,0.001239334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008885682,"about_ca_system_score_gemma":0.000001712206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007542416,"about_ca_topic_score_gemma":0.000006017673,"domain_scores_codex":[0.9960917,0.00007801176,0.0006185608,0.00107141,0.001149153,0.0009911826],"domain_scores_gemma":[0.998461,0.0001080191,0.0002503895,0.0008017488,0.000001825784,0.0003770227],"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":[0.001566285,0.005728574,0.2718227,0.0003573531,0.003003322,0.0004083125,0.02188563,0.2878338,0.0007325698,0.006003405,0.1280131,0.272645],"study_design_scores_gemma":[0.02643246,0.003025615,0.4114127,0.0005856047,0.002050245,0.00006317687,0.04570713,0.1254478,0.005238547,0.1103594,0.2623333,0.007344015],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08423927,0.0005258272,0.7786798,0.0005068971,0.0007835548,0.004443109,0.0002563627,0.0003320118,0.1302331],"genre_scores_gemma":[0.644066,0.0001778131,0.3510004,0.000704188,0.00007669268,0.0005261175,0.0001203296,0.0000847372,0.00324374],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5598267,"threshold_uncertainty_score":0.9996646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1590777061088341,"score_gpt":0.2991424911721349,"score_spread":0.1400647850633008,"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."}}