{"id":"W1973112475","doi":"10.3138/carto.42.4.285","title":"Digital Sketch-Map Drawing as an Instrument to Collect Data about Spatial Cognition","year":2007,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Spatial Cognition and Navigation","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Sketch; Computer science; Field (mathematics); Process (computing); Visualization; Cognitive map; Formative assessment; Spatial cognition; Human–computer interaction; Data science; Cognition; Information retrieval; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.003770103,0.0006251006,0.0003521013,0.005005326,0.0007517916,0.001366828,0.0007541422,0.0004418207,0.005575905],"category_scores_gemma":[0.01946172,0.0003255683,0.0003053382,0.004661586,0.001553547,0.002103817,0.001712782,0.0008251726,0.0008070639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004508592,"about_ca_system_score_gemma":0.0008296655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001423707,"about_ca_topic_score_gemma":0.002758468,"domain_scores_codex":[0.9963958,0.002135523,0.0002143789,0.0003638291,0.0008070963,0.00008337989],"domain_scores_gemma":[0.9845418,0.01002776,0.0007792749,0.002976891,0.001266619,0.0004076023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001156331,0.0008557994,0.05488665,0.002020242,0.0001635035,0.0004759684,0.04355658,0.005604444,0.0472075,0.02477037,0.01107521,0.8082274],"study_design_scores_gemma":[0.001234741,0.00626215,0.3371373,0.001227119,0.0004549187,0.00342829,0.07543621,0.05748345,0.09999903,0.09085318,0.3255414,0.0009422225],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5685771,0.001119234,0.3917273,0.0004151129,0.0001834818,0.003477199,0.006391256,0.001365077,0.02674426],"genre_scores_gemma":[0.5012649,0.0008820805,0.4888526,0.000118073,0.00005386141,0.003273391,0.002203491,0.0001351429,0.003216484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005575905,"threshold_uncertainty_score":0.01993841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01527786395374692,"score_gpt":0.2910280787417429,"score_spread":0.2757502147879959,"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."}}