{"id":"W2611480772","doi":"10.1145/3025453.3025554","title":"Collection Objects","year":2017,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Selection (genetic algorithm); Workflow; Context (archaeology); Object (grammar); Action (physics); Data collection; Human–computer interaction; Artificial intelligence; Database; Mathematics","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":[0.00003295197,0.00003083085,0.00003133186,0.00002174808,0.0003624448,0.000205017,0.0004369327,0.0000122775,0.00003720338],"category_scores_gemma":[0.00003714337,0.0000256134,0.00002324831,0.00002138887,0.00001199953,0.0006928344,0.0001076315,0.00002957526,0.0003149154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001296403,"about_ca_system_score_gemma":0.0000156383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008749995,"about_ca_topic_score_gemma":0.00002170812,"domain_scores_codex":[0.9997319,0.000006318156,0.00003080648,0.0001027737,0.00005137405,0.0000768352],"domain_scores_gemma":[0.9995375,0.00001014659,0.00003346461,0.0003504129,0.000049402,0.00001912856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002310657,0.0001404849,0.006726937,0.000007516066,0.00005905241,0.00004495208,0.002293738,0.000003816371,0.1665568,0.6382551,0.1683421,0.01754647],"study_design_scores_gemma":[0.000364418,0.0001224494,0.3065664,0.00000937861,0.00000258233,0.0000183112,0.0001064074,0.01154303,0.668016,0.003891212,0.009175614,0.0001841687],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.007970152,0.000003351103,0.2483095,0.0008924132,0.0006841148,0.00003708233,1.090042e-7,0.00001376202,0.7420895],"genre_scores_gemma":[0.9873392,0.000001218384,0.001721899,0.0003690574,0.00002598369,0.000002181854,1.358249e-7,0.000001161283,0.01053919],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.979369,"threshold_uncertainty_score":0.4047705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01702142720915436,"score_gpt":0.2825565180690802,"score_spread":0.2655350908599259,"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."}}