{"id":"W6921646108","doi":"10.7486/dri.s7526c40b","title":"Returning Irish Migrants collection: Interview 015","year":2015,"lang":"en","type":"other","venue":"Digital Repository of Ireland","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Irish; Qualitative research; Immigration; Data collection; Northern ireland","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002025203,0.0004990014,0.0008645322,0.0004540621,0.0000665519,0.0002141737,0.000393683,0.0004856768,0.0001531834],"category_scores_gemma":[0.0001925652,0.0004720037,0.0002507263,0.0004783218,0.0002687991,0.0002410702,0.0001454114,0.0003580574,0.001020108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000212533,"about_ca_system_score_gemma":0.000266901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001636927,"about_ca_topic_score_gemma":0.00007926409,"domain_scores_codex":[0.9975401,0.0001158623,0.0006546867,0.0005658892,0.0007914855,0.0003319435],"domain_scores_gemma":[0.9978539,0.00005204184,0.000947769,0.0006629624,0.0002333717,0.0002499538],"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":[0.0000663259,0.0001159783,0.003447745,0.0002828829,0.000326868,0.0001329085,0.0001856015,6.996042e-7,0.0001083489,0.000001024908,0.994667,0.0006646215],"study_design_scores_gemma":[0.0007887112,0.0001983057,0.0002950316,0.002786706,0.0001190754,0.0003751424,0.00008156148,0.00001055701,0.0002019103,0.00001731092,0.9946336,0.0004921415],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001511874,0.01027752,0.000007925609,0.000008884484,0.001467134,0.0003929752,0.0004484968,0.0004977246,0.9853874],"genre_scores_gemma":[0.0218989,0.00004015592,0.0000525538,0.00001044844,0.0006033948,0.0000188451,0.0002356189,0.001116527,0.9760236],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02038703,"threshold_uncertainty_score":0.9997731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02387157322950736,"score_gpt":0.2547691177233906,"score_spread":0.2308975444938832,"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."}}