{"id":"W2269673471","doi":"10.6084/m9.figshare.1603143.v1","title":"Socio Economic Change of Barasat: A Case Study Berunanpukuria","year":2015,"lang":"en","type":"dataset","venue":"Figshare","topic":"Social and Economic Development in India","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Socioeconomics; Population; Census; Quarter (Canadian coin); Economic growth; Distribution (mathematics); Agriculture; Agricultural economics; Sociology; Archaeology; Demography; Economics","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":[0.0003400933,0.0004012025,0.0003452907,0.001219851,0.004722029,0.002007423,0.001296286,0.001003175,0.003213729],"category_scores_gemma":[0.000552161,0.0002558905,0.0004383025,0.002658499,0.001751569,0.0007974508,0.002347878,0.001108652,0.0002861223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00548821,"about_ca_system_score_gemma":0.001743235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1047556,"about_ca_topic_score_gemma":0.2193446,"domain_scores_codex":[0.9995019,0.0001238968,0.00001620857,0.00004507991,0.00005723214,0.0002557183],"domain_scores_gemma":[0.9996626,0.0000671342,0.00008033264,0.00001524099,0.00004055065,0.0001341744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0002685119,0.001412768,0.1822756,0.001123175,0.0001463653,0.3649878,0.377455,0.001835957,0.004199333,0.007667613,0.006014111,0.05261386],"study_design_scores_gemma":[0.00001434497,0.0003141005,0.3250161,0.0003635479,0.00006484747,0.02041021,0.6192324,0.0007683227,0.0005595746,0.0004524614,0.03275231,0.00005175148],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9938838,0.0006120737,0.00008994802,0.0004925271,0.00001836558,0.00003728528,0.00009510413,0.000004152393,0.004766742],"genre_scores_gemma":[0.9949532,0.001330315,0.0002207949,0.0001333884,0.00002187695,0.0000232739,0.00008687276,0.000005057777,0.003225122],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.1047556,"threshold_uncertainty_score":0.2082917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2288695708289107,"score_gpt":0.3779076510097139,"score_spread":0.1490380801808031,"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."}}