{"id":"W4400076042","doi":"10.3390/genealogy8030079","title":"A ‘Usable Past’?: Irish Affiliation in CANZUS Settler States","year":2024,"lang":"en","type":"article","venue":"Genealogy","topic":"Irish and British Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Irish; USable; Genealogy; Political science; History; Computer science; World Wide Web; Linguistics; Philosophy","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":[0.00103553,0.0001078153,0.000219984,0.00117102,0.005972099,0.003580988,0.0005580066,0.0006381627,0.004628009],"category_scores_gemma":[0.002878421,0.0001582605,0.00008265575,0.002087374,0.003900912,0.001584712,0.003054847,0.001401941,0.000325162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003599407,"about_ca_system_score_gemma":0.001625191,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3227125,"about_ca_topic_score_gemma":0.5870907,"domain_scores_codex":[0.9992052,0.0002840165,0.00001903629,0.00007288252,0.0001329158,0.0002860029],"domain_scores_gemma":[0.9991899,0.0001954446,0.0001935189,0.00004756584,0.0001356884,0.0002378346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00007449628,0.00006115299,0.1075993,0.00003790953,0.00001223459,0.0008140488,0.8646899,0.00002031072,0.0004442502,0.00532421,0.002232659,0.01868952],"study_design_scores_gemma":[0.00000329292,0.00002745677,0.1348611,0.00006529425,0.00000603319,0.0001620884,0.8473866,0.00003148928,0.00008947701,0.0002261051,0.01712654,0.00001441987],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9807674,0.0002329183,0.00004359693,0.0009749979,0.00002691403,0.000004656601,0.00003056025,0.000001720714,0.01791724],"genre_scores_gemma":[0.9946307,0.0002861728,0.00004030031,0.0002450757,0.00001056928,0.00000565022,0.00003551965,0.00000417208,0.004741979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6772875,"threshold_uncertainty_score":0.6416682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01610173585573551,"score_gpt":0.3107886603123646,"score_spread":0.2946869244566291,"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."}}