{"id":"W4409346411","doi":"10.1111/jiec.70023","title":"The updated and improved method for water scarcity impact assessment in LCA, AWARE2.0","year":2025,"lang":"en","type":"article","venue":"Journal of Industrial Ecology","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Total; Hydro-Québec; L'Oreal USA","keywords":"Scarcity; Industrial ecology; Water scarcity; Natural resource economics; Environmental science; Business; Environmental economics; Environmental resource management; Economics; Sustainability; Water resources; Ecology; Microeconomics","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":[0.004300862,0.001399564,0.001046106,0.004474364,0.0007334027,0.003209493,0.001493095,0.001089661,0.01629538],"category_scores_gemma":[0.0166749,0.0009711625,0.002311128,0.004367389,0.0004250359,0.003044374,0.001778905,0.002314757,0.005863179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001026586,"about_ca_system_score_gemma":0.002249118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01211042,"about_ca_topic_score_gemma":0.01217215,"domain_scores_codex":[0.9967622,0.00102705,0.0002356319,0.0004689544,0.00137175,0.0001345315],"domain_scores_gemma":[0.9941658,0.001902243,0.0002809311,0.001325927,0.002238363,0.00008673996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002417438,0.0002475085,0.01580765,0.001314625,0.0006223216,0.0002568225,0.000361598,0.1937913,0.005950734,0.06539091,0.1932065,0.5228082],"study_design_scores_gemma":[0.0001275679,0.00009889717,0.007359496,0.0002726578,0.0002134296,0.0002726681,0.0002170923,0.6087408,0.01210184,0.05461202,0.3157001,0.000283398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01193446,0.0006868087,0.9340373,0.000556342,0.0007181664,0.0004087246,0.01461267,0.0165966,0.02044889],"genre_scores_gemma":[0.1252588,0.0007777716,0.8279997,0.0005468571,0.0002904675,0.001235947,0.02258928,0.008384367,0.01291676],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01629538,"threshold_uncertainty_score":0.05451345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0133368223876921,"score_gpt":0.3382097571711218,"score_spread":0.3248729347834298,"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."}}