{"id":"W4406795318","doi":"10.1007/978-981-97-4784-9_39","title":"Developing Cognitive Abilities in Robots: A Bibliometric Overview of AI and ML Applications","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in electrical engineering","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Cognition; Cognitive science; Psychology; Computer science; Artificial intelligence; Neuroscience","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.0001740741,0.0002179497,0.0005297046,0.01157409,0.00001971459,0.00001107865,0.00006172113,0.0003925271,0.0000209342],"category_scores_gemma":[0.001524989,0.0002208599,0.00005903102,0.007439587,0.00003655877,0.00003801095,0.00002777798,0.0008770493,0.000002083271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003659214,"about_ca_system_score_gemma":0.0004444378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002050536,"about_ca_topic_score_gemma":0.00007792579,"domain_scores_codex":[0.9986776,0.0000103607,0.0005767228,0.0003100348,0.0001712208,0.000254073],"domain_scores_gemma":[0.9979993,0.001541694,0.00007342553,0.0001371573,0.0001892528,0.00005921942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004980719,0.00005150972,0.003086263,0.003068472,0.00005667321,0.00000856131,0.0003563638,0.001867031,0.00008182575,0.03424679,0.000008436821,0.9571183],"study_design_scores_gemma":[0.001935458,0.002793374,0.04564944,0.07708279,0.001478893,0.0003350962,0.000155375,0.1736595,0.05228069,0.6051487,0.03371005,0.005770578],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003793283,0.1148494,0.870998,0.002690861,0.0002344345,0.002661998,0.00001886841,0.0001155338,0.004637619],"genre_scores_gemma":[0.9795145,0.0130305,0.005155413,0.0009129583,0.0002674666,0.0002633036,0.00007056813,0.00006416603,0.0007211294],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9757212,"threshold_uncertainty_score":0.9996288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09402896158017109,"score_gpt":0.3919604155351708,"score_spread":0.2979314539549997,"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."}}