{"id":"W4200205145","doi":"10.18280/ijsdp.160707","title":"Water Resilience in the Indian Context: Definitions, Policies, Approaches and Gaps","year":2021,"lang":"en","type":"article","venue":"International Journal of Sustainable Development and Planning","topic":"Water resources management and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Resilience (materials science); Corporate governance; Context (archaeology); Water resources; Delphi method; Environmental resource management; Integrated water resources management; Environmental planning; Population; Business; Environmental science; Geography; Computer science; Sociology; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004553789,0.0006372313,0.0006107085,0.007686359,0.003927624,0.01025869,0.002071481,0.001667391,0.002530546],"category_scores_gemma":[0.006340706,0.0003542144,0.0005799372,0.0115212,0.01238428,0.009620786,0.008287185,0.004182272,0.0002135806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01432355,"about_ca_system_score_gemma":0.02107985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02248193,"about_ca_topic_score_gemma":0.02321763,"domain_scores_codex":[0.9959819,0.001756793,0.0003394316,0.0003635705,0.0008233801,0.0007348193],"domain_scores_gemma":[0.9946271,0.003209033,0.0006431444,0.0002360386,0.0008016345,0.0004831628],"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":[0.00003851748,0.0001028624,0.00996377,0.002933804,0.0000432605,0.001027075,0.03488537,0.004059486,0.0005071476,0.8273656,0.008128346,0.1109449],"study_design_scores_gemma":[0.000004810427,0.00009220979,0.02273074,0.00863189,0.00007997797,0.001757046,0.2482491,0.00515597,0.0008574684,0.4540771,0.2581934,0.0001703438],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.190465,0.1983602,0.04849534,0.2664014,0.001836983,0.0004135684,0.001088669,0.0002082591,0.2927307],"genre_scores_gemma":[0.9194348,0.06436189,0.009398773,0.003094249,0.0002808186,0.0001842003,0.000177563,0.00003032035,0.003037364],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.02248193,"threshold_uncertainty_score":0.1039252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02392136111365955,"score_gpt":0.211340224373267,"score_spread":0.1874188632596075,"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."}}