{"id":"W4308045318","doi":"10.1145/3568732","title":"A chronology of SIGCHI conferences","year":2022,"lang":"en","type":"article","venue":"interactions","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Manitoba; University of Guelph; University of Saskatchewan; Ontario Tech University","funders":"","keywords":"IBM; Library science; State (computer science); Engineering; Art history; Management; Art; Computer science; Physics","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":[0.007477969,0.001289556,0.0008590888,0.02028338,0.005763118,0.01746541,0.001772647,0.002482058,0.07021657],"category_scores_gemma":[0.0175824,0.0009214551,0.000645529,0.02426476,0.002095585,0.008098589,0.004246984,0.006495515,0.04745334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003129177,"about_ca_system_score_gemma":0.008026556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007601368,"about_ca_topic_score_gemma":0.01612496,"domain_scores_codex":[0.9934372,0.001002117,0.001004968,0.000731811,0.002978143,0.0008456802],"domain_scores_gemma":[0.9730012,0.002869904,0.001797689,0.001605635,0.01331704,0.007408508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001135051,0.00006041255,0.001518521,0.001375999,0.00001565157,0.0001721451,0.0008177494,0.0001315314,0.0008545709,0.009411714,0.7910666,0.1944614],"study_design_scores_gemma":[0.000007272253,0.00003690817,0.002486535,0.0004851034,0.000004959047,0.000134096,0.0006350438,0.0000322669,0.0001068876,0.0008772245,0.995176,0.0000177508],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.008251372,0.212127,0.01475027,0.06556261,0.2292351,0.002260047,0.02838815,0.00649565,0.4329298],"genre_scores_gemma":[0.06508844,0.2909857,0.05055341,0.03010008,0.06857988,0.004776941,0.04641651,0.004374872,0.4391242],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07021657,"threshold_uncertainty_score":0.2348978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01194841471593702,"score_gpt":0.2240271810300121,"score_spread":0.212078766314075,"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."}}