{"id":"W2137920714","doi":"10.29173/iq888","title":"Data in Development: An Overview of Microdata on Developing Countries","year":2010,"lang":"en","type":"article","venue":"IASSIST Quarterly","topic":"Microfinance and Financial Inclusion","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Microdata (statistics); Computer science; Data science; Environmental health; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005256714,0.0007298423,0.001294388,0.01535054,0.000679351,0.002467646,0.0009880216,0.0009537839,0.009140301],"category_scores_gemma":[0.02411578,0.0007759092,0.0008046746,0.05091605,0.0003955297,0.003044335,0.002240526,0.001200569,0.003993039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001184675,"about_ca_system_score_gemma":0.003825957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01166341,"about_ca_topic_score_gemma":0.007122572,"domain_scores_codex":[0.9944372,0.001309158,0.001563827,0.0005637959,0.001792974,0.0003329453],"domain_scores_gemma":[0.9743134,0.008794198,0.004989958,0.00523932,0.005730342,0.0009329064],"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":[0.0005171446,0.0001862834,0.1148025,0.007528554,0.0004524281,0.0002132851,0.0008235585,0.003010865,0.001600571,0.02401841,0.4722275,0.3746189],"study_design_scores_gemma":[0.00004879774,0.00003674094,0.1067129,0.001420017,0.0001430647,0.0001949753,0.0005221977,0.0005410314,0.001884414,0.006206423,0.8822204,0.00006898076],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"review","genre_scores_codex":[0.01251412,0.01879151,0.02273237,0.002543287,0.0003530754,0.0006865052,0.9228258,0.001435291,0.01811806],"genre_scores_gemma":[0.05540097,0.03464898,0.04371088,0.001231106,0.0005563942,0.002625944,0.8560164,0.0006879179,0.005121341],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01535054,"threshold_uncertainty_score":0.03057742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1311141523470521,"score_gpt":0.3132564839107914,"score_spread":0.1821423315637393,"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."}}