{"id":"W4403443325","doi":"10.48550/arxiv.2408.03943","title":"Building Machines that Learn and Think with People","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"AI in Service Interactions","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Cambridge Trust; Natural Sciences and Engineering Research Council of Canada; Alan Turing Institute; European Commission; Leverhulme Trust; National Science Foundation","keywords":"Psychology; Computer science","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":[0.006694668,0.0006472514,0.0005946187,0.001216423,0.002422166,0.006693704,0.001834829,0.00323224,0.006988425],"category_scores_gemma":[0.01924618,0.0007152989,0.001092961,0.0008303789,0.01281343,0.02065693,0.007540536,0.003168692,0.003591614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001345781,"about_ca_system_score_gemma":0.002785648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002129842,"about_ca_topic_score_gemma":0.00150388,"domain_scores_codex":[0.995491,0.002474953,0.0001389787,0.0008904064,0.000674301,0.0003304241],"domain_scores_gemma":[0.9916041,0.003481237,0.0006536053,0.002717479,0.0006123377,0.0009313005],"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":[0.00003629543,0.00009373717,0.002131898,0.0001220336,0.00006658431,0.000124645,0.006236577,0.005613575,0.001254145,0.9441023,0.005709245,0.03450885],"study_design_scores_gemma":[0.00002555646,0.00002757592,0.000336686,0.0000626421,0.00001826921,0.00008315311,0.001125621,0.01428505,0.0008351906,0.9369312,0.04623988,0.00002922431],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05325403,0.001380886,0.8441647,0.02585543,0.000295815,0.0002266893,0.0001286444,0.001702944,0.07299089],"genre_scores_gemma":[0.5818157,0.001020297,0.4019504,0.002075522,0.0001970873,0.0004020163,0.0002878978,0.0003786125,0.01187249],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006988425,"threshold_uncertainty_score":0.03540522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0462153179255044,"score_gpt":0.1981232866788791,"score_spread":0.1519079687533747,"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."}}