{"id":"W2008082665","doi":"10.1145/2598153.2598158","title":"Analyzing intended use effects in target acquisition","year":2014,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Fitts's law; Replicate; Movement (music); Computer science; Target acquisition; Variation (astronomy); Work (physics); Style (visual arts); Human–computer interaction; Artificial intelligence; Statistics; Mathematics; Engineering; Geography","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":[0.005137834,0.0005426233,0.0005653428,0.001421296,0.0003256115,0.001477959,0.0005694971,0.0006633922,0.003624316],"category_scores_gemma":[0.08505358,0.0005205947,0.0005764483,0.001044286,0.0006916559,0.001475092,0.001522609,0.000967214,0.0005557103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006015314,"about_ca_system_score_gemma":0.0003344408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002128187,"about_ca_topic_score_gemma":0.001890663,"domain_scores_codex":[0.9960128,0.001841082,0.0002803745,0.0006929164,0.001006171,0.0001667323],"domain_scores_gemma":[0.8862563,0.09927582,0.004940364,0.005538451,0.003351981,0.0006371193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008608388,0.001323113,0.4277812,0.001560259,0.0007230561,0.0005667271,0.01393472,0.01310231,0.2613205,0.00716127,0.001117442,0.262801],"study_design_scores_gemma":[0.00009104219,0.001706262,0.9408174,0.00006885752,0.0003154736,0.0005866754,0.0007727863,0.01896011,0.03211101,0.002965978,0.001511921,0.00009257057],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9784955,0.0003314842,0.01604769,0.00003755628,0.0000154359,0.00009545477,0.0002613654,0.0001482124,0.004567214],"genre_scores_gemma":[0.9897569,0.0001150236,0.008306107,0.00003313768,0.000009554681,0.0002128888,0.0002560563,0.0001846367,0.00112565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005137834,"threshold_uncertainty_score":0.02717179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008109836757988131,"score_gpt":0.2410148458350022,"score_spread":0.2329050090770141,"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."}}