{"id":"W305492262","doi":"10.4018/ijmhci.2015070104","title":"Which Way is Up?","year":2015,"lang":"en","type":"article","venue":"International Journal of Mobile Human Computer Interaction","topic":"Spatial Cognition and Navigation","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Affordance; Interactivity; Focus (optics); Locative case; Computer science; Variety (cybernetics); Affect (linguistics); Social media; Mobilities; Sense of place; Relation (database); Human–computer interaction; Cognitive psychology; Sociology; Multimedia; Psychology; Communication; Linguistics; Artificial intelligence; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001444783,0.0003929621,0.0003412557,0.0007771694,0.006740723,0.008470132,0.0006448209,0.001344952,0.0228186],"category_scores_gemma":[0.003919106,0.0001770715,0.0004310189,0.0008284091,0.00717287,0.01074528,0.003588476,0.002368107,0.006553962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001833478,"about_ca_system_score_gemma":0.001539014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004805835,"about_ca_topic_score_gemma":0.0105124,"domain_scores_codex":[0.9987979,0.0005187512,0.00003927368,0.0001954801,0.0002335338,0.0002150745],"domain_scores_gemma":[0.998785,0.0002528214,0.0001474192,0.0001382484,0.0003089127,0.0003676996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000143915,0.00005440111,0.01061498,0.0003954051,0.00004291114,0.001551572,0.2313964,0.0001166774,0.001434946,0.4406957,0.1252093,0.1883438],"study_design_scores_gemma":[0.000004507483,0.00003478706,0.002374934,0.0003826509,0.00001663685,0.0008902184,0.1683764,0.00008120068,0.0003796619,0.04130584,0.7861173,0.00003581036],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08239684,0.0118354,0.01421558,0.1115153,0.007668062,0.00006085068,0.000404959,0.0003904151,0.7715126],"genre_scores_gemma":[0.8293976,0.007956014,0.004561217,0.01127203,0.0006025973,0.0000546802,0.0002460822,0.0003094195,0.1456004],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0228186,"threshold_uncertainty_score":0.07633579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03374380204803364,"score_gpt":0.3126507764562272,"score_spread":0.2789069744081936,"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."}}