{"id":"W4385616792","doi":"10.1177/00420980231186499","title":"What might working from home mean for the geography of work and commuting in the Greater Golden Horseshoe, Canada?","year":2023,"lang":"en","type":"article","venue":"Urban Studies","topic":"Work-Family Balance Challenges","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Toronto Metropolitan University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Residence; Downtown; Work (physics); Geography; Human geography; Demographic economics; Economic geography; Urban sprawl; Pandemic; Telecommuting; Economic growth; Coronavirus disease 2019 (COVID-19); Economics; Urban planning; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009909731,0.0001103451,0.0002286134,0.00005365147,0.0006123803,0.00008709416,0.0003632709,0.00003874351,0.000002916768],"category_scores_gemma":[0.0001144693,0.00006403852,0.00004904693,0.0005832966,0.0004342376,0.00008719836,0.0001299767,0.0001131179,5.20319e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004589269,"about_ca_system_score_gemma":0.00003607911,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0714865,"about_ca_topic_score_gemma":0.8070168,"domain_scores_codex":[0.9988555,0.0001686247,0.0001721634,0.0001760007,0.0002966548,0.0003311119],"domain_scores_gemma":[0.996835,0.002811925,0.0000836262,0.000197972,0.00005052159,0.00002096902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000007999133,0.000003922324,0.8548644,0.000007884966,0.0001120447,0.000001988432,0.1240026,0.000003275019,5.165704e-7,0.0001447754,0.01910138,0.001749227],"study_design_scores_gemma":[0.000123674,0.000007078077,0.6895825,0.0001842911,0.00002906075,4.202273e-8,0.2926686,0.000001269421,0.000001977914,0.0009541582,0.01636722,0.0000800933],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9301544,0.05899368,7.028088e-7,0.00931355,0.0006388745,0.000356016,0.000008733657,0.00003246765,0.0005015616],"genre_scores_gemma":[0.9909653,0.008343751,0.00001995357,0.0001892445,0.000255748,0.00007364793,0.000001949179,0.000009044647,0.0001413449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7355304,"threshold_uncertainty_score":0.9346966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07090044304863234,"score_gpt":0.2987793808236193,"score_spread":0.227878937774987,"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."}}