{"id":"W1534152511","doi":"10.1007/978-3-540-79474-5_2","title":"A Quest for Adaptable and Interpretable Architectures of Computational Intelligence","year":2008,"lang":"en","type":"book-chapter","venue":"Studies in computational intelligence","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fuzzy logic; Computer science; Artificial intelligence; Artificial neural network; Cognitive science; Machine learning; Psychology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005344811,0.0004765546,0.0007714448,0.0004829904,0.0002394289,0.00005528473,0.0008225762,0.0001805717,0.00001372826],"category_scores_gemma":[0.0002691056,0.0004797732,0.0001514849,0.0001723024,0.0007270728,0.0001535963,0.0005526976,0.0004646545,0.00001078699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001244117,"about_ca_system_score_gemma":0.0003182732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003619949,"about_ca_topic_score_gemma":0.00003368446,"domain_scores_codex":[0.9971973,0.00005194059,0.001016502,0.0008534367,0.0005134791,0.0003673529],"domain_scores_gemma":[0.9943315,0.00406919,0.0005024885,0.000305697,0.0007062745,0.00008481538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003595099,0.00002568581,0.00003776982,0.0002995387,0.0001521677,0.00001848853,0.003581063,0.7096599,3.536552e-7,0.253792,0.0008894122,0.0315076],"study_design_scores_gemma":[0.00007688682,0.0002502464,0.00002588094,0.001283663,0.00001697216,0.00008293213,0.00008991831,0.3989856,0.00004476015,0.5957609,0.002965727,0.0004165214],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000051906,0.01580605,0.9730393,0.0003089614,0.0004502211,0.0005333027,0.00009165568,0.00008075366,0.0096379],"genre_scores_gemma":[0.3643596,0.002019414,0.6229511,0.0004249581,0.0001674837,0.0001062398,0.00009848611,0.00006992458,0.009802792],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3643076,"threshold_uncertainty_score":0.9997654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09133730792856361,"score_gpt":0.3385263802328255,"score_spread":0.2471890723042619,"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."}}