{"id":"W4414180050","doi":"10.1177/00420980251361626","title":"Profiling caregivers: Caregiving workload, mobility, stress, and remote work difficulties","year":2025,"lang":"en","type":"article","venue":"Urban Studies","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Fondo Nacional de Desarrollo Científico y Tecnológico; Centro de Desarrollo Urbano Sustentable","keywords":"Profiling (computer programming); Socioeconomic status; Variety (cybernetics); Work (physics); Multivariate analysis; Multivariate statistics; Survey data collection; Focus group","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001144928,0.0003520773,0.0003175112,0.0009178359,0.001012817,0.0009454979,0.0002868309,0.0002880377,0.001341074],"category_scores_gemma":[0.005482879,0.0001584805,0.0003716881,0.0008467064,0.0003849124,0.0006597696,0.001460891,0.0004556735,0.0001561088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000556215,"about_ca_system_score_gemma":0.0008515108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009878866,"about_ca_topic_score_gemma":0.01212187,"domain_scores_codex":[0.9994829,0.0001964952,0.00007834906,0.00005724786,0.00007841888,0.0001065172],"domain_scores_gemma":[0.9989048,0.0002715423,0.0004238623,0.00006578292,0.0001539841,0.0001800046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003214653,0.0000321172,0.9856185,0.00004971816,0.00003150066,0.0002019139,0.004827095,0.0001400679,0.0001071287,0.0001251018,0.0002935505,0.008541325],"study_design_scores_gemma":[0.000003317362,0.00006543196,0.9623016,0.0001410859,0.00002641707,0.0004483212,0.03461661,0.0007520985,0.0001400418,0.0004794717,0.001007219,0.00001843062],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983645,0.0002712361,0.0002580662,0.0001952889,0.0000073913,0.00001445133,0.0001499587,0.000001795802,0.0007373801],"genre_scores_gemma":[0.9992921,0.0002434597,0.0001793963,0.00002070266,0.000004775814,0.00001579256,0.0001227929,7.458066e-7,0.0001201555],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009878866,"threshold_uncertainty_score":0.01964277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05163220019836862,"score_gpt":0.3836458836293186,"score_spread":0.33201368343095,"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."}}