{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001892576,0.0001024146,0.00012663,0.0002575201,0.00002302523,0.0001191429,0.0002304797,0.00005052484,0.0003238472],"category_scores_gemma":[0.00001444003,0.0001008501,0.00008599116,0.0000835742,0.000010199,0.000593856,0.00002796332,0.0002468435,0.0001194886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000230037,"about_ca_system_score_gemma":0.00002036793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001103468,"about_ca_topic_score_gemma":0.00001316684,"domain_scores_codex":[0.9989264,0.0000276426,0.0004464834,0.00007995246,0.000436721,0.00008282383],"domain_scores_gemma":[0.9983463,0.00003152078,0.0001774077,0.00007063748,0.001279815,0.00009428354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004244116,0.0004488778,0.002026744,0.0000428023,0.001221283,0.00008402338,0.009104885,0.1954895,0.01656512,0.0008068513,0.3594744,0.4143112],"study_design_scores_gemma":[0.01000766,0.002399491,0.01162076,0.001171395,0.0001534538,0.003052344,0.001539679,0.3690979,0.135857,0.006039503,0.4577807,0.001280128],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9019845,0.00006605031,0.07518397,0.0002281278,0.01767418,0.00009536778,0.000007162594,0.0001021274,0.004658529],"genre_scores_gemma":[0.996977,0.00001805378,0.0006699437,0.0001861583,0.002020774,0.000004999762,0.00002148087,0.00001686997,0.00008473024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.413031,"threshold_uncertainty_score":0.4112548,"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."}}