{"id":"W2579963809","doi":"10.1145/3025453.3025500","title":"Subtle and Personal Workspace Requirements for Visual Search Tasks on Public Displays","year":2017,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Workspace; Computer science; Human–computer interaction; Visual search; Multimedia; Computer vision; Artificial intelligence; Robot","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002303883,0.0005102003,0.000337653,0.0005926018,0.0007187261,0.001911525,0.0007374813,0.0006319905,0.004812371],"category_scores_gemma":[0.04017643,0.0003353701,0.0003181478,0.0003726988,0.0004800478,0.002077461,0.00233963,0.0004549933,0.0004007934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003237487,"about_ca_system_score_gemma":0.0003625365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001085416,"about_ca_topic_score_gemma":0.001982406,"domain_scores_codex":[0.9977205,0.0009340115,0.0002590342,0.0002314616,0.0006127422,0.0002421469],"domain_scores_gemma":[0.9616362,0.03012201,0.002809628,0.002305891,0.001828657,0.00129752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003971403,0.0009676276,0.1573877,0.003390632,0.0001543788,0.001453809,0.07385452,0.02316453,0.3981982,0.02944041,0.004253679,0.303763],"study_design_scores_gemma":[0.0005126807,0.00412875,0.6505659,0.0007900716,0.0003869584,0.00578498,0.04945441,0.1312398,0.09267316,0.03199155,0.03192705,0.0005446175],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9439142,0.0001817392,0.04720673,0.0001464265,0.000007120916,0.00007573504,0.0001204589,0.0004869525,0.007860653],"genre_scores_gemma":[0.9839113,0.00005107668,0.01522964,0.00001682607,0.00000559878,0.00009124656,0.0001388306,0.0001027712,0.0004526912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004812371,"threshold_uncertainty_score":0.01609898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08107354485505121,"score_gpt":0.3731802812340155,"score_spread":0.2921067363789643,"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."}}