{"id":"W3021468410","doi":"10.1371/journal.pone.0232409","title":"Similar social presence effects when reaching for real and digital objects","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Action Observation and Synchronization","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Object (grammar); Observer (physics); Computer vision; Artificial intelligence; Computer science; Space (punctuation); Matching (statistics); Image (mathematics); Psychology; Cognitive psychology; Communication; Mathematics; Physics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00004955407,0.00006786237,0.0001194862,0.00001770877,0.0001157918,0.00005166294,0.00005201742,0.00006844596,0.00006983844],"category_scores_gemma":[0.0003052977,0.00007179417,0.00002071686,0.00005573537,0.0000226092,0.0001915897,0.00002159082,0.00007771839,0.00003307505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001655008,"about_ca_system_score_gemma":0.00001092891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007111264,"about_ca_topic_score_gemma":0.000002322564,"domain_scores_codex":[0.9994351,0.00003819296,0.0001069536,0.0001880877,0.0001159361,0.0001156904],"domain_scores_gemma":[0.9996079,0.0001683775,0.0000562365,0.00006195174,0.00004706537,0.00005847285],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.002331223,0.005493012,0.2574875,0.003373877,0.002574232,0.00005197479,0.3252211,0.00002128058,0.09674019,0.05702091,0.1303969,0.1192878],"study_design_scores_gemma":[0.03422362,0.007581496,0.7155141,0.0008649002,0.001797069,0.00001759131,0.01367864,0.1063739,0.03801695,0.02752167,0.04989708,0.004513047],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9638329,0.00005024429,0.0112565,0.007278717,0.0001200462,0.0007573694,0.00003432232,0.0002334944,0.01643641],"genre_scores_gemma":[0.9967775,0.000005345511,0.0009052809,0.0009445091,0.000407271,0.00004378737,0.00005347034,0.00001699817,0.000845839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4580265,"threshold_uncertainty_score":0.2927682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1083083029266152,"score_gpt":0.2889964792465626,"score_spread":0.1806881763199474,"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."}}