{"id":"W6908033938","doi":"10.25549/impa-m14614","title":"Market, Unyamwezi, Tanzania [s.d.]","year":2012,"lang":"en","type":"dataset","venue":"University of Southern California Digital Library","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Plank; Tanzania; Front (military); Quarter (Canadian coin); Table (database); Government (linguistics)","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":[0.0003610949,0.001147486,0.0009025391,0.002792209,0.0005363778,0.001800114,0.001232167,0.0007945206,0.0500273],"category_scores_gemma":[0.003598551,0.0004534489,0.0006305051,0.007564697,0.0002098585,0.0009261558,0.0008490134,0.0008916105,0.04360335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009341505,"about_ca_system_score_gemma":0.002333903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08976946,"about_ca_topic_score_gemma":0.1213477,"domain_scores_codex":[0.9997198,0.00003586905,0.00004463175,0.00009238332,0.00005723741,0.0000500366],"domain_scores_gemma":[0.9989572,0.0002027192,0.0002381428,0.0001463927,0.0003181113,0.0001375179],"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":[0.0001094076,0.000009902998,0.002737535,0.0008443541,0.00003326591,0.00003236852,0.00002937611,0.0001415209,0.00005923501,0.0002630174,0.9922763,0.00346384],"study_design_scores_gemma":[0.0002588336,0.00001961142,0.02168129,0.0005993845,0.00006703413,0.0000848273,0.0001238028,0.0003029571,0.0002254087,0.0004042535,0.9762102,0.00002248947],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002105224,0.0001415459,0.00001716484,0.00006286702,0.00001234292,0.000003366581,0.9989032,0.00009514053,0.000553919],"genre_scores_gemma":[0.001031199,0.0002056387,0.00009497401,0.00005398482,0.000009721063,0.00003038312,0.997251,0.00003153517,0.001291595],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08976946,"threshold_uncertainty_score":0.1784939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007836397576814477,"score_gpt":0.1747255206724897,"score_spread":0.1668891230956752,"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."}}