{"id":"W4328022419","doi":"10.46609/ijsser.2023.v08i02.003","title":"IMMEDIATE EFFECTS OF COVID-19 PANDEMIC SITUATION ON LIVELIHOOD OF WOMEN CULTIVATORS IN THE COASTAL AREAS OF WEST BENGAL AND ODISHA","year":2023,"lang":"en","type":"article","venue":"International Journal of Social Science and Economic Research","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Livelihood; Poverty; Agriculture; Development economics; Unemployment; Population; Pandemic; Geography; Economic growth; Quarter (Canadian coin); Socioeconomics; Coronavirus disease 2019 (COVID-19); Economics; Sociology; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009415495,0.00006148528,0.000259923,0.0009678543,0.00009135131,0.00004897191,0.0004935878,0.00005092035,0.00002728616],"category_scores_gemma":[0.003816111,0.00005391613,0.00004413725,0.0003890728,0.000643854,0.0003527426,0.0001318086,0.0002137778,0.00000674779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006105099,"about_ca_system_score_gemma":0.0005608393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007601246,"about_ca_topic_score_gemma":0.00008037412,"domain_scores_codex":[0.9986578,0.00006763688,0.000583927,0.0001569622,0.0002883069,0.0002453674],"domain_scores_gemma":[0.997987,0.001135463,0.0005252874,0.00006360751,0.0001791521,0.0001094901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002709162,0.0001177843,0.9127911,0.00009790353,0.0000682388,0.00001031267,0.04752021,0.0001893398,0.002181909,0.0321063,0.0002594571,0.004386467],"study_design_scores_gemma":[0.001447856,0.000321888,0.9664358,0.00004523591,0.000002057948,0.000009030683,0.005892653,0.0006522796,0.0003970653,0.02431986,0.0004040143,0.00007217459],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975236,0.00006198855,0.00001377494,0.001515084,0.000184289,0.0001217499,0.00004983382,0.000001524172,0.0005281235],"genre_scores_gemma":[0.9991714,0.0006008398,0.000004319812,0.0001027632,0.00009938245,0.000004643972,0.000001618041,0.000003852863,0.00001117351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05364472,"threshold_uncertainty_score":0.4568517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1027630184148986,"score_gpt":0.396355006625157,"score_spread":0.2935919882102584,"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."}}