{"id":"W2540318822","doi":"","title":"\"Synchrony\" as a Way to Choose an Interacting Partner","year":2012,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"NeuroDevNet","funders":"","keywords":"Robot; Mechanism (biology); Focus (optics); Artificial intelligence; Human–robot interaction; Human–computer interaction; Computer science; Robotics; Social robot; Architecture; Mobile robot; Robot control","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":[0.002995511,0.0005729372,0.0003948814,0.0007203316,0.001752942,0.003671624,0.0009548982,0.001418279,0.02575972],"category_scores_gemma":[0.01343087,0.0002357963,0.0003970225,0.000655622,0.001501145,0.006472685,0.005011675,0.00146945,0.004974024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003180162,"about_ca_system_score_gemma":0.000669823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002227585,"about_ca_topic_score_gemma":0.0004568338,"domain_scores_codex":[0.9980456,0.0007847297,0.0001365684,0.0003673089,0.0004658141,0.0001999853],"domain_scores_gemma":[0.9950637,0.002068886,0.0004926328,0.0007130702,0.0006445576,0.001017075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00205245,0.0002563884,0.008725938,0.000476733,0.00007610963,0.0008775748,0.007763505,0.00317432,0.06612661,0.5203609,0.02347399,0.3666355],"study_design_scores_gemma":[0.0004722691,0.001766921,0.009090398,0.0003300439,0.0002895504,0.002390913,0.01165614,0.0709203,0.04013778,0.7085156,0.1541624,0.0002675988],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2106807,0.0007695978,0.5874118,0.009467898,0.002223985,0.0003637701,0.0003077579,0.002478093,0.1862964],"genre_scores_gemma":[0.8779104,0.0001750217,0.09563052,0.000618346,0.0001632272,0.0002268982,0.000195839,0.0003819984,0.02469762],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02575972,"threshold_uncertainty_score":0.08617485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03536634185535443,"score_gpt":0.2953230827262082,"score_spread":0.2599567408708537,"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."}}