{"id":"W3086749368","doi":"","title":"THE IMPACT OF COVID-19 ON VICTORIAN SHARE HOUSEHOLDS","year":2020,"lang":"en","type":"article","venue":"Minerva Access (University of Melbourne)","topic":"Housing, Finance, and Neoliberalism","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Casual; Quarter (Canadian coin); Unemployment; Mental health; Context (archaeology); Demographic economics; Coronavirus disease 2019 (COVID-19); Feeling; Population; Vulnerability (computing); Pandemic; Business; Psychology; Economic growth; Medicine; Geography; Economics; Political science; Environmental health; Social psychology; Psychiatry","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":[0.000819559,0.0001224649,0.0001847421,0.0003508491,0.001538421,0.001373614,0.000586196,0.0004564967,0.004052336],"category_scores_gemma":[0.004041063,0.0001627948,0.0002029256,0.0008935934,0.00076155,0.0007369635,0.003934674,0.0008440586,0.0002573512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007402212,"about_ca_system_score_gemma":0.004809463,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5317478,"about_ca_topic_score_gemma":0.6775776,"domain_scores_codex":[0.9986035,0.0003689528,0.00003476099,0.00006658567,0.0002442167,0.0006818806],"domain_scores_gemma":[0.998137,0.0001674098,0.0004231993,0.00006171962,0.0003578126,0.0008528252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004148672,0.0002882857,0.8893331,0.0002940443,0.00007937086,0.001822192,0.0209286,0.001263901,0.001122409,0.007206923,0.01393682,0.06330949],"study_design_scores_gemma":[0.000003467197,0.00005887664,0.9834421,0.00009210001,0.000005905295,0.0001062405,0.009599663,0.0005029202,0.00005961487,0.0002822071,0.005839512,0.000007392532],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866977,0.0004425755,0.00007323149,0.002790895,0.00001983686,0.0000285446,0.0006873937,0.000003068886,0.009256596],"genre_scores_gemma":[0.9969928,0.0002626576,0.00004226169,0.0002029788,0.000008339187,0.00001319924,0.0002271049,0.000002046369,0.002248688],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5317478,"threshold_uncertainty_score":0.9420198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08233476350392925,"score_gpt":0.2623491955536555,"score_spread":0.1800144320497262,"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."}}