{"id":"W1997044328","doi":"10.3138/carto.49.3.2185","title":"A User Study of Experimental Maps for Outdoor Activities","year":2014,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digital mapping; Computer science; Representation (politics); Terrain; Quality (philosophy); Cartography; Data science; Information retrieval; Geography; Human–computer interaction; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006534796,0.001049593,0.0007360711,0.001655958,0.002423847,0.001523799,0.00106786,0.001344714,0.005203591],"category_scores_gemma":[0.03157194,0.000619771,0.0006399574,0.001644684,0.001726277,0.002117017,0.002106988,0.001063802,0.0008837365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007316938,"about_ca_system_score_gemma":0.0004992069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003076305,"about_ca_topic_score_gemma":0.004318104,"domain_scores_codex":[0.9931406,0.005216827,0.0002736615,0.0004377781,0.0005774842,0.0003536298],"domain_scores_gemma":[0.9504784,0.03987019,0.001687185,0.003911034,0.003061904,0.0009912653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.004725595,0.01425048,0.177673,0.00149649,0.0001870822,0.003985364,0.6749227,0.001460199,0.01983232,0.001685384,0.00419476,0.09558664],"study_design_scores_gemma":[0.0006447779,0.0329418,0.2639561,0.0003218101,0.0002391475,0.003572871,0.6258311,0.00609765,0.02257403,0.001406848,0.04191982,0.0004941664],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975561,0.00001946209,0.001027569,0.0000388447,0.000007712437,0.0001493492,0.0001123291,0.0000365801,0.001051955],"genre_scores_gemma":[0.9948758,0.00006266923,0.002934061,0.00005582269,0.00001599669,0.0004680739,0.000205255,0.00003747747,0.001344827],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006534796,"threshold_uncertainty_score":0.03455973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01769088130792414,"score_gpt":0.3317562878640321,"score_spread":0.314065406556108,"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."}}