{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002536818,0.002347663,0.001567899,0.002667507,0.002136626,0.006641793,0.004124597,0.001507543,0.05137299],"category_scores_gemma":[0.006037822,0.001351331,0.002053967,0.00321913,0.001163277,0.007125516,0.006802804,0.001542188,0.01891676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001031392,"about_ca_system_score_gemma":0.002122968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00296521,"about_ca_topic_score_gemma":0.002895295,"domain_scores_codex":[0.9974184,0.0003302805,0.0003387112,0.0006053496,0.001094704,0.0002125264],"domain_scores_gemma":[0.9955707,0.001015252,0.0002878889,0.001829262,0.0009270852,0.0003697593],"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":[0.001185231,0.0003188957,0.004059948,0.002359827,0.0001979256,0.00091431,0.00308129,0.003182762,0.02558562,0.09248612,0.1544099,0.7122183],"study_design_scores_gemma":[0.00008887937,0.0001929193,0.001307236,0.0002169139,0.00009270247,0.0005868016,0.0003054434,0.007636665,0.02270301,0.01554088,0.9511997,0.0001289011],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007222811,0.001801111,0.8201708,0.0004589826,0.0005571283,0.001659733,0.005587464,0.1113153,0.05122662],"genre_scores_gemma":[0.09523734,0.002901821,0.7295533,0.001337671,0.0003699338,0.002935937,0.02554795,0.0332913,0.1088247],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05137299,"threshold_uncertainty_score":0.1718598,"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."}}