{"id":"W4298038908","doi":"","title":"Analysing LCIA methods for water use impacts","year":2015,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Université Laval","funders":"","keywords":"Computer science; Environmental science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01548495,0.001262894,0.0008257456,0.005289077,0.0004790796,0.002219137,0.000925776,0.0008774729,0.004387256],"category_scores_gemma":[0.04679244,0.0006597514,0.001788886,0.004079258,0.001080072,0.001598969,0.0023825,0.001490094,0.0008732766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001454737,"about_ca_system_score_gemma":0.001407037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004241634,"about_ca_topic_score_gemma":0.002425005,"domain_scores_codex":[0.986895,0.006113465,0.0005452908,0.001180462,0.004885586,0.0003803451],"domain_scores_gemma":[0.94797,0.03954334,0.003456741,0.003246896,0.005634368,0.0001486612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001020099,0.000264329,0.08230273,0.002633638,0.001794641,0.0001613389,0.001868018,0.2477878,0.03524369,0.07501381,0.002490701,0.5494192],"study_design_scores_gemma":[0.00009834839,0.0007167835,0.06805499,0.0004946685,0.0005107679,0.0003038133,0.0008366504,0.775784,0.06303589,0.05636469,0.03357495,0.0002245777],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05400789,0.001449018,0.9360576,0.0002154262,0.00006655389,0.0003867565,0.0009556912,0.0008745803,0.005986415],"genre_scores_gemma":[0.4856224,0.00110454,0.5053906,0.000176464,0.0001407164,0.001648491,0.001911582,0.0007736403,0.003231586],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01548495,"threshold_uncertainty_score":0.08189321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02913491606767846,"score_gpt":0.3065346193944598,"score_spread":0.2773997033267813,"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."}}