{"id":"W2942562418","doi":"","title":"Components of population change (persons), Queensland, June quarter 1981 to December quarter 2018","year":2006,"lang":"en","type":"article","venue":"","topic":"Migration, Aging, and Tourism Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Population; Geography; Demography; Archaeology; Sociology","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":[0.00064558,0.0008698427,0.0005602046,0.004860078,0.00114794,0.0009303307,0.001175702,0.0005192009,0.0214572],"category_scores_gemma":[0.00491271,0.0005910238,0.0007970762,0.01008823,0.0003480877,0.0009296648,0.001508567,0.001584979,0.006286967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006676704,"about_ca_system_score_gemma":0.007687349,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5891094,"about_ca_topic_score_gemma":0.5904924,"domain_scores_codex":[0.9985077,0.00008739839,0.0002177607,0.0001531171,0.0007280998,0.0003060113],"domain_scores_gemma":[0.9971299,0.0001331902,0.0007630803,0.00007850436,0.001483627,0.0004117302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0005658876,0.0002698319,0.427422,0.002110857,0.0002784249,0.0003013567,0.002154612,0.001687412,0.0007697043,0.0009918635,0.513966,0.049482],"study_design_scores_gemma":[0.00002357798,0.0000423012,0.9656294,0.00008374025,0.00001790303,0.00005576617,0.0004146736,0.0001155225,0.00004644709,0.00002674766,0.03353521,0.000008740716],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.204265,0.003772559,0.0005509072,0.002595585,0.001449766,0.0009289922,0.7379829,0.0006010865,0.04785314],"genre_scores_gemma":[0.3785591,0.006687436,0.001188121,0.0008156565,0.0004769209,0.002699807,0.4666415,0.0001221946,0.1428093],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5891094,"threshold_uncertainty_score":0.8266208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02770650782963634,"score_gpt":0.2833659630182448,"score_spread":0.2556594551886085,"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."}}