{"id":"W2339186592","doi":"10.14288/1.0064925","title":"Moving target selection in interactive video","year":2010,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Cursor (databases); Pointer (user interface); Selection (genetic algorithm); Computer vision; Kinematics; Artificial intelligence; Task (project management); Human–computer interaction; Engineering","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":[0.0006480924,0.0007140178,0.000560286,0.0007257015,0.0002292834,0.0008179219,0.0007838252,0.0005259434,0.005822706],"category_scores_gemma":[0.005429747,0.0001880906,0.0003276302,0.0004150427,0.000231616,0.0007902307,0.0006601306,0.0002189852,0.0008160636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000240539,"about_ca_system_score_gemma":0.0001418583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002071055,"about_ca_topic_score_gemma":0.00197495,"domain_scores_codex":[0.9994304,0.000183504,0.00002414487,0.0001052362,0.000198453,0.00005821935],"domain_scores_gemma":[0.9963474,0.002859161,0.0001977618,0.0001917846,0.0002956412,0.0001083734],"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":[0.006536923,0.0008479038,0.01975023,0.001561735,0.0002364696,0.001293931,0.003738652,0.03409382,0.4300066,0.002391067,0.004179364,0.4953632],"study_design_scores_gemma":[0.0006691439,0.01409526,0.1670405,0.0004004243,0.000544873,0.004779669,0.003680351,0.4786712,0.2944787,0.00360252,0.03148054,0.0005568397],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9203694,0.0003244093,0.07376922,0.00004098621,0.00002827845,0.0001574261,0.0003121487,0.001591453,0.003406544],"genre_scores_gemma":[0.9483995,0.0002618422,0.04742127,0.00003471574,0.00001617052,0.0001610496,0.0004791879,0.0002482181,0.002978012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005822706,"threshold_uncertainty_score":0.01947892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004387331880828312,"score_gpt":0.1834037596733093,"score_spread":0.1790164277924809,"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."}}