{"id":"W7099938275","doi":"","title":"GOVERNMENT MACHINERIES AND PROGRAMMES RELEVANT TO WOMEN","year":2016,"lang":"en","type":"article","venue":"","topic":"Microfinance and Financial Inclusion","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agency (philosophy); Government (linguistics); Advice (programming); Wish","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001169723,0.0001363451,0.0001849298,0.001420031,0.002261437,0.002086312,0.0004090793,0.001192201,0.08948101],"category_scores_gemma":[0.009612625,0.000118532,0.0001268772,0.002964262,0.0006366607,0.001827096,0.001518613,0.001280598,0.005881453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002450701,"about_ca_system_score_gemma":0.006102587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009855694,"about_ca_topic_score_gemma":0.02450206,"domain_scores_codex":[0.9985233,0.0005165723,0.00006027412,0.0001047102,0.0002894606,0.0005057011],"domain_scores_gemma":[0.9938637,0.001485512,0.0009560431,0.0003727223,0.0008719877,0.002450115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001063879,0.0003076862,0.06325838,0.0003853084,0.00001302701,0.0006352802,0.02680664,0.0001363,0.0003871826,0.1708686,0.5491109,0.1879843],"study_design_scores_gemma":[0.000008487091,0.00005758861,0.05764391,0.0003268968,0.000005655912,0.0002489085,0.02795606,0.00009898865,0.0001239737,0.004235962,0.9092821,0.00001151465],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.177236,0.007795615,0.0008540909,0.1442795,0.003166803,0.0003691035,0.005136974,0.0001148196,0.6610472],"genre_scores_gemma":[0.6069982,0.004656396,0.0009435633,0.01107245,0.0008960146,0.0004676004,0.001420859,0.00006383705,0.3734811],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.08948101,"threshold_uncertainty_score":0.2993438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01168380046451101,"score_gpt":0.1973910687919956,"score_spread":0.1857072683274845,"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."}}