{"id":"W6886038647","doi":"10.14288/1.0225402","title":"Correspondence and other records regarding immigration","year":2016,"lang":"en","type":"article","venue":"Open Collections","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Inheritance (genetic algorithm); Census; Historical record; Refugee","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":[0.001867146,0.000544774,0.0004988846,0.008786165,0.006997504,0.002190077,0.001464283,0.0008022105,0.286595],"category_scores_gemma":[0.01470196,0.0003989516,0.0002218191,0.01686683,0.0007846357,0.001169101,0.00174372,0.001121734,0.09774753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005607699,"about_ca_system_score_gemma":0.03204006,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4925177,"about_ca_topic_score_gemma":0.6024397,"domain_scores_codex":[0.9967318,0.0003626577,0.0002876447,0.0002998552,0.001777523,0.0005405284],"domain_scores_gemma":[0.9877508,0.00133216,0.0007583281,0.001441037,0.007751816,0.0009659618],"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":[0.00004454772,0.00002882538,0.00145467,0.0002420989,0.000003126888,0.0001832182,0.002444031,0.00003474002,0.0004086124,0.004418082,0.9500334,0.04070467],"study_design_scores_gemma":[0.000005091498,0.000005608184,0.005154373,0.000103457,0.000002692248,0.00004627352,0.001110096,0.00002369534,0.0001316999,0.0002549472,0.9931517,0.00001050707],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.008100853,0.0009336059,0.000999142,0.002647537,0.001524255,0.001604663,0.2050856,0.0008494606,0.7782548],"genre_scores_gemma":[0.01973172,0.001851854,0.002404479,0.0008498702,0.0004060809,0.0007276796,0.08019985,0.0004203515,0.8934081],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5074823,"threshold_uncertainty_score":0.9793018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0212649367745735,"score_gpt":0.2714244303617036,"score_spread":0.2501594935871301,"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."}}