{"id":"W4398897020","doi":"10.7910/dvn/u1jec0","title":"Replication Data for: Material interests, identity, and linked fate in three countries","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Metallurgy and Cultural Artifacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Replication (statistics); Identity (music); Biology; Art; Virology","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":[0.00577031,0.00128924,0.001263719,0.00284396,0.001957178,0.002490347,0.003343236,0.001908777,0.1252402],"category_scores_gemma":[0.04693767,0.0008271648,0.001557747,0.0058483,0.0007813259,0.001129012,0.002686235,0.002648094,0.07511126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001715006,"about_ca_system_score_gemma":0.005563595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04149264,"about_ca_topic_score_gemma":0.0682198,"domain_scores_codex":[0.9967893,0.0009806874,0.000547928,0.0006837389,0.0006706683,0.0003276991],"domain_scores_gemma":[0.9786617,0.005559328,0.001476454,0.007744452,0.005605175,0.0009529356],"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":[0.0001333975,0.00003058048,0.002134649,0.0004060844,0.00004633107,0.00002508103,0.000089557,0.0001083486,0.00005851699,0.001054046,0.9934228,0.002490717],"study_design_scores_gemma":[0.001055915,0.00005621751,0.02148614,0.0008006088,0.0001320061,0.0001017193,0.0004674552,0.0002474262,0.0004153385,0.003804949,0.9713331,0.00009905332],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005194988,0.00003212026,0.00026002,0.0001371197,0.00004402642,0.0001037435,0.9975769,0.0001605708,0.001165948],"genre_scores_gemma":[0.002498356,0.00004491203,0.001032526,0.0001063985,0.00002154783,0.001511365,0.9916431,0.0001648325,0.002977151],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1252402,"threshold_uncertainty_score":0.4189703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1136913293787682,"score_gpt":0.362328015340162,"score_spread":0.2486366859613938,"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."}}