{"id":"W4405577738","doi":"10.21203/rs.3.rs-5639090/v1","title":"On process-based granular reconstruction of life cycle inventories: sustainably coherent planning of primary battery-grade nickel","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sustainability; Nickel; Battery (electricity); Process (computing); Life-cycle assessment; Primary (astronomy); Process engineering; Reliability engineering; Environmental science; Metallurgy; Materials science; Computer science; Engineering; Economics; Production (economics); Thermodynamics; Macroeconomics; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001505138,0.0009990361,0.001423238,0.000864888,0.0005419016,0.002137276,0.001444845,0.001355135,0.001659998],"category_scores_gemma":[0.005430649,0.001093281,0.00112565,0.00143175,0.001405782,0.001846461,0.001352329,0.001185228,0.0001682892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001656433,"about_ca_system_score_gemma":0.001688436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02680454,"about_ca_topic_score_gemma":0.01667674,"domain_scores_codex":[0.9995554,0.0001412737,0.00002704224,0.00009491084,0.0001013009,0.00008007216],"domain_scores_gemma":[0.9978825,0.001527843,0.0001818656,0.0001481209,0.0001646018,0.00009494403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002729994,0.000009701139,0.00017609,0.00001343323,0.00001013996,0.00001813528,0.00001573436,0.994908,0.0001586777,0.002316923,0.00005926391,0.002286447],"study_design_scores_gemma":[0.000002333466,0.000004889733,0.00005011439,0.000002168968,0.000001960718,0.00000171501,0.000005421343,0.9968948,0.00009073064,0.002900341,0.00004348739,0.000002016475],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09969162,0.0004044758,0.8957345,0.0003344025,0.00003638113,0.00007841757,0.0003522194,0.0002842542,0.003083654],"genre_scores_gemma":[0.897953,0.0002326218,0.0999078,0.00006190987,0.00002379572,0.0001126084,0.0004254202,0.0001101772,0.001172673],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02680454,"threshold_uncertainty_score":0.05329704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04737962174686851,"score_gpt":0.363955634498,"score_spread":0.3165760127511315,"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."}}