{"id":"W6959587534","doi":"10.1111/1539-6924.00256/abstract","title":"Life Cycle Impact Assessment: A Challenge for Risk Analysts","year":2002,"lang":"en","type":"article","venue":"Research Showcase @ Carnegie Mellon University (Carnegie Mellon University)","topic":"Legal and Regulatory Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Work (physics); Government (linguistics); Population; Limiting; Matching (statistics); Noise (video)","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","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003500363,0.000580461,0.0009515229,0.002884948,0.00584024,0.0003526513,0.002089991,0.0006845261,0.001877709],"category_scores_gemma":[0.0009007428,0.000631447,0.001481462,0.00562,0.00191252,0.001830739,0.0006466531,0.001496461,0.0002079763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00314374,"about_ca_system_score_gemma":0.001615635,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02006105,"about_ca_topic_score_gemma":0.009334523,"domain_scores_codex":[0.989916,0.00387538,0.0003719216,0.001497322,0.002164359,0.002175058],"domain_scores_gemma":[0.9929947,0.001502549,0.0003813773,0.001154653,0.001485179,0.002481554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.005122621,0.0110935,0.04451627,0.001214615,0.01757493,0.02166098,0.1151402,0.02856696,0.002246379,0.4610273,0.2198911,0.07194509],"study_design_scores_gemma":[0.004147729,0.0008063489,0.0007926945,0.00009340439,0.001122201,0.000006100477,0.07012746,0.01934425,0.0001059568,0.0008159717,0.9013335,0.001304452],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5186459,0.001376236,0.002163713,0.006412028,0.0005991903,0.002480301,0.0005487483,0.0007269285,0.4670469],"genre_scores_gemma":[0.9293225,0.007967911,0.0003239664,0.00003588536,0.00054665,0.0000018103,0.00005407795,0.00005452244,0.06169267],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6814423,"threshold_uncertainty_score":0.9996137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1026569076669055,"score_gpt":0.3734589700668737,"score_spread":0.2708020623999682,"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."}}