{"id":"W1982222965","doi":"10.5539/ibr.v3n2p136","title":"Fertility, Health and Female Labour Force Participation in Urban Cameroon","year":2010,"lang":"en","type":"article","venue":"International Business Research","topic":"Global Maternal and Child Health","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fertility; Economics; Labour supply; Demographic economics; Population; Labour economics; Affect (linguistics); Demography; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007231687,0.000072927,0.0001464541,0.0002409226,0.0000804527,0.00004518027,0.0001168039,0.00005794984,0.0001846638],"category_scores_gemma":[0.000499273,0.00006182227,0.00001505257,0.0003400686,0.00009612554,0.000115489,0.0001050961,0.0004464403,0.00004839678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001133523,"about_ca_system_score_gemma":0.0002644066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004177646,"about_ca_topic_score_gemma":0.001429071,"domain_scores_codex":[0.9985423,0.00006159363,0.0002409789,0.0002272846,0.0005997714,0.0003280791],"domain_scores_gemma":[0.9989332,0.00006449121,0.00003652091,0.0001446849,0.0005990987,0.0002220333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00028695,0.0002271192,0.9885896,0.0001744178,0.000008103763,0.00002171016,0.0003594794,0.000002321886,0.002463765,0.002900908,0.0003834228,0.004582172],"study_design_scores_gemma":[0.0007241082,0.00008206247,0.9899504,0.0001158005,8.934934e-7,0.00001716545,0.00008528045,0.0001588173,0.0002548515,0.001140765,0.007423743,0.00004613866],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9729242,0.0001213155,0.00001744388,0.02398207,0.000260028,0.0002738946,0.00001236572,0.00001825018,0.002390468],"genre_scores_gemma":[0.9967797,0.00008689825,0.000131863,0.000884268,0.0001903091,0.00002781166,0.00003393543,0.000009287201,0.00185589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02385558,"threshold_uncertainty_score":0.6315379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07185199666812507,"score_gpt":0.4477060036536621,"score_spread":0.375854006985537,"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."}}