{"id":"W2768392484","doi":"10.12691/jsa-1-1-9","title":"Women and Climate Change in Bangladesh: An Analysis From Gender Perspective","year":2017,"lang":"en","type":"article","venue":"Cross-cultural communication","topic":"Climate Change, Adaptation, Migration","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climate change; Perspective (graphical); Gender analysis; Political economy of climate change; Gender relations; Phenomenon; Geography; Political science; Development economics; Sociology; Gender studies; Economics; 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":[0.0008624791,0.0002303305,0.0003462696,0.001106012,0.001626347,0.001166376,0.0002158945,0.0004984019,0.006901164],"category_scores_gemma":[0.001816272,0.0001335697,0.0004289829,0.002569752,0.0009557242,0.001045116,0.001190107,0.0005451545,0.0004322158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001484288,"about_ca_system_score_gemma":0.001195317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01724329,"about_ca_topic_score_gemma":0.02521914,"domain_scores_codex":[0.9992398,0.0003682086,0.00003629347,0.00004898159,0.00009739721,0.0002092999],"domain_scores_gemma":[0.9987921,0.0006620713,0.0002333761,0.00002525806,0.0001257861,0.0001615381],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003096314,0.0001311646,0.7968764,0.0004734409,0.0001688845,0.00244734,0.1279137,0.0004420604,0.0009573506,0.02207867,0.003538694,0.04466277],"study_design_scores_gemma":[0.0000122007,0.0002680802,0.6619026,0.0003601156,0.0001248589,0.001162282,0.2891925,0.0004980235,0.0002348314,0.002803244,0.04339965,0.00004155794],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9568312,0.005315155,0.0004407,0.003675514,0.00005667825,0.00003940542,0.0005756402,0.000003399427,0.03306238],"genre_scores_gemma":[0.9947397,0.003032863,0.00009584745,0.0001737677,0.00002299411,0.00002900619,0.00008323099,0.000002520804,0.001820136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01724329,"threshold_uncertainty_score":0.03428584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1935620567944533,"score_gpt":0.4261984316910267,"score_spread":0.2326363748965735,"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."}}