{"id":"W4403315730","doi":"10.4017/gt.2024.23.s.894.5.sp","title":"Conducting agetech research with marginalized and underserved communities: Challenging assumptions","year":2024,"lang":"en","type":"article","venue":"Gerontechnology","topic":"Innovative Approaches in Technology and Social Development","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Erasmus+; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Sociology; Psychology; Computer science; Gerontology; Data science; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001218818,0.000166097,0.0002123174,0.001000057,0.0008108843,0.0001871579,0.0003223903,0.000321104,0.00008891781],"category_scores_gemma":[0.00008575121,0.0001474792,0.00002282799,0.001186425,0.001115671,0.0004294247,0.0005331002,0.001127469,0.00008576027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001032798,"about_ca_system_score_gemma":0.00003814832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003101565,"about_ca_topic_score_gemma":0.000353392,"domain_scores_codex":[0.9987643,0.00003435701,0.0001996591,0.0002853473,0.0001760982,0.0005402424],"domain_scores_gemma":[0.9993568,0.0001284916,0.0000505378,0.0002781843,0.0001792957,0.000006692224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001576235,0.00002612578,0.001338267,0.0002380638,0.000107245,0.00004803618,0.0006858539,0.000001276984,0.00031952,0.9821205,0.0006352692,0.01446407],"study_design_scores_gemma":[0.001773839,0.0001542975,0.002429661,0.001112524,0.0001171871,0.0001643187,0.254373,0.005955112,0.001211553,0.3914185,0.3400071,0.001282893],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9352241,0.00197172,0.008483973,0.0138979,0.0003372524,0.0005409427,0.000001634739,0.002212904,0.03732961],"genre_scores_gemma":[0.9973525,0.0001189058,0.001591573,0.0002232517,0.0001114934,0.0001491986,0.00001630705,0.0000337292,0.0004030061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5907019,"threshold_uncertainty_score":0.6236748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3550473789162655,"score_gpt":0.34675014806807,"score_spread":0.008297230848195503,"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."}}