{"id":"W4366550140","doi":"10.1145/3544548.3581426","title":"Memory Tracer & Memory Compass: Investigating Personal Location Histories as a Design Material for Everyday Reminiscence","year":2023,"lang":"en","type":"article","venue":"","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Reminiscence; Compass; Computer science; Resource (disambiguation); Human–computer interaction; Recall; Process (computing); Overlay; Data science; Psychology; Cognitive psychology; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008743298,0.0002015508,0.0002027049,0.0003212934,0.0003838879,0.0001544163,0.0006008677,0.0001503686,0.0001159259],"category_scores_gemma":[0.0005884096,0.0002008675,0.00004720727,0.0008746186,0.000222928,0.0009189357,0.0001526925,0.000198569,0.000330349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002926731,"about_ca_system_score_gemma":0.0002443562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003879293,"about_ca_topic_score_gemma":0.00002450161,"domain_scores_codex":[0.9983163,0.0001113711,0.00037226,0.00053299,0.0003067485,0.0003603038],"domain_scores_gemma":[0.9985533,0.0003346306,0.0002235174,0.00038455,0.000455786,0.0000482038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001789716,0.0001549532,0.0001755824,0.0002557221,0.0001259468,0.00002431488,0.04080675,0.0006829609,0.5236378,0.1355135,0.275498,0.02294548],"study_design_scores_gemma":[0.001313788,0.0005793798,0.001489665,0.0002192587,0.00003529435,0.0001927773,0.004176908,0.1162549,0.8225768,0.03106278,0.02088236,0.001216108],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1380349,0.00001443346,0.8500034,0.004579967,0.003087929,0.0007038797,0.000005063977,0.001619586,0.001950924],"genre_scores_gemma":[0.8281299,0.000001312928,0.1598891,0.0007701679,0.0002515508,0.0003400083,0.00004045627,0.00002738466,0.01055011],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6901142,"threshold_uncertainty_score":0.8191139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0831180725621834,"score_gpt":0.3145648124386455,"score_spread":0.2314467398764621,"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."}}