{"id":"W6887797931","doi":"10.17863/cam.113816","title":"Building machines that learn and think with people.","year":2024,"lang":"en","type":"article","venue":"Apollo (University of Cambridge)","topic":"Embodied and Extended Cognition","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Cambridge Trust; Natural Sciences and Engineering Research Council of Canada; Alan Turing Institute; European Commission; Engineering and Physical Sciences Research Council; Leverhulme Trust; National Science Foundation","keywords":"Construct (python library); Complement (music); Cognition; Trustworthiness; Cognitive robotics; Cognitive systems; Path (computing); Work (physics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006553174,0.0004714403,0.0002570562,0.0003971451,0.000586345,0.001968431,0.0006453948,0.001011485,0.009407278],"category_scores_gemma":[0.002763527,0.0003207915,0.0004337392,0.0001920639,0.003795033,0.00420688,0.002275225,0.001438944,0.00242416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005760844,"about_ca_system_score_gemma":0.0004752693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001033499,"about_ca_topic_score_gemma":0.001275417,"domain_scores_codex":[0.9996465,0.0001089728,0.00001594875,0.0001140161,0.00008171389,0.00003279588],"domain_scores_gemma":[0.9991423,0.0004518808,0.0000431081,0.0002348946,0.00006027871,0.0000675217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006090206,0.00003902515,0.0006887658,0.00041764,0.0000614833,0.0001539068,0.00131646,0.005303336,0.008525026,0.8357863,0.02234322,0.1253039],"study_design_scores_gemma":[0.00002233413,0.00003521068,0.0008529531,0.0001852553,0.00002512277,0.0002365879,0.000185579,0.008081885,0.00890841,0.8064975,0.1749391,0.00003020154],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03555649,0.01595484,0.7349169,0.01434289,0.001142767,0.00007204589,0.0003206292,0.003312147,0.1943812],"genre_scores_gemma":[0.5476496,0.007465669,0.3801662,0.001624821,0.0003526033,0.0002191908,0.0005047728,0.0007186682,0.06129843],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009407278,"threshold_uncertainty_score":0.03147048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01670458198377712,"score_gpt":0.2166448389477285,"score_spread":0.1999402569639513,"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."}}