{"id":"W2103488373","doi":"10.32920/ryerson.14636922","title":"User Task Scenarios for Map-Based Decision Support in Community Health Planning","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Usability; Task (project management); Thematic map; Computer science; Think aloud protocol; Thematic analysis; Process (computing); Human–computer interaction; Data science; Geography; Qualitative research; Cartography; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.006544339,0.0002066944,0.0005599519,0.0003675917,0.001384014,0.0002559661,0.0005247748,0.0003151885,0.00009591357],"category_scores_gemma":[0.0005483907,0.0002033664,0.0001927502,0.0003173809,0.0001135893,0.0001692842,0.0004922951,0.0007570029,0.00001425716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003719572,"about_ca_system_score_gemma":0.001622683,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08161867,"about_ca_topic_score_gemma":0.1673369,"domain_scores_codex":[0.9972329,0.0005825416,0.000848298,0.0002349929,0.0006000039,0.0005012887],"domain_scores_gemma":[0.9975742,0.0009389651,0.0004340051,0.0005027212,0.0004260277,0.0001241549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000117842,0.0004276366,0.3717237,0.002745654,0.0001675969,0.0000102892,0.5073891,0.01624313,0.000001560485,0.00668239,0.08736502,0.007126121],"study_design_scores_gemma":[0.002123096,0.0001739389,0.07600412,0.003247856,0.00002319591,9.824302e-7,0.5515027,0.001794577,0.000006225755,0.002564937,0.3616042,0.0009541871],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.633785,0.001690611,0.244067,0.02722627,0.0109761,0.01396221,0.0004542721,0.001064977,0.0667735],"genre_scores_gemma":[0.9842486,0.00004539364,0.01240971,0.001841184,0.0000903096,0.0003065705,0.0003324046,0.00001498269,0.0007108361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3504636,"threshold_uncertainty_score":0.9999161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06611628542918398,"score_gpt":0.3846181678697581,"score_spread":0.3185018824405741,"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."}}