{"id":"W177018550","doi":"","title":"Reducción del riesgo de desastres bajo las actuales y cambiantes condiciones climáticas","year":2008,"lang":"es","type":"article","venue":"Arcimis (State Meteorological Agency)","topic":"Environmental and Ecological Studies","field":"Energy","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"University of Cambridge; Government of Ontario; World Bank Group","keywords":"Political science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001344287,0.0003974131,0.0004268324,0.000643252,0.000235759,0.0006986301,0.0002787409,0.0006587162,0.004648828],"category_scores_gemma":[0.003875121,0.0002291426,0.0006088582,0.0006714308,0.0003026313,0.0003653785,0.0004622703,0.0005721906,0.0003197497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002613144,"about_ca_system_score_gemma":0.0003822633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01222912,"about_ca_topic_score_gemma":0.01872714,"domain_scores_codex":[0.9997085,0.0001058699,0.00002348952,0.00006822244,0.00004521013,0.00004879415],"domain_scores_gemma":[0.9986721,0.0003278947,0.0005021233,0.0002078749,0.0001452208,0.0001447573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004276751,0.0002245605,0.9419286,0.000274885,0.0005366068,0.0002713133,0.0004573437,0.0004747124,0.00253731,0.0009121021,0.001274445,0.0468314],"study_design_scores_gemma":[0.00007413036,0.0004500238,0.9920118,0.00008019784,0.0004313267,0.0005079576,0.0004754047,0.0005848191,0.0003366735,0.00061439,0.00442365,0.000009638238],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899845,0.004724032,0.0002893433,0.0005609723,0.00003006214,0.00001218786,0.0007678992,0.00003964999,0.003591197],"genre_scores_gemma":[0.993711,0.003319654,0.0003187055,0.00007921707,0.00004501453,0.000007466404,0.0005342964,0.000008486501,0.001976184],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01222912,"threshold_uncertainty_score":0.02431589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03545390263485619,"score_gpt":0.246149543611199,"score_spread":0.2106956409763429,"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."}}