{"id":"W4250463482","doi":"10.4018/978-1-4666-0261-8.ch009","title":"Adaptive Computation Paradigm in Knowledge Representation","year":2012,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Artificial intelligence; Representation (politics); Computational intelligence; Data science; Paradigm shift; Computation; Evolutionary computation; Software; Theoretical computer science; Human–computer interaction; Machine learning","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":[0.0002334279,0.0003715779,0.0004061584,0.0001445512,0.0000894026,0.000114305,0.0005009695,0.00031506,0.000005072272],"category_scores_gemma":[0.00001328003,0.0004099817,0.0001564287,0.00007882217,0.00007062611,0.0001385457,0.0004071597,0.0003874942,0.0003129331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003290158,"about_ca_system_score_gemma":0.0001584728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004598403,"about_ca_topic_score_gemma":0.0001129379,"domain_scores_codex":[0.9981067,0.0000865828,0.0004292724,0.0006804017,0.0002847662,0.0004123165],"domain_scores_gemma":[0.9988469,0.0001909312,0.0002707291,0.0004018194,0.0001424584,0.0001471289],"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":[0.00001220177,0.00001610761,0.00003572586,0.000006856571,0.00002403681,0.0000239516,0.0002468771,0.0001020549,4.365714e-7,0.7385384,0.0008803742,0.260113],"study_design_scores_gemma":[0.0006887582,0.0001290614,0.001436796,0.0005812091,0.00003970528,0.00006122235,0.000008946279,0.0468159,0.00001409095,0.9439595,0.005500648,0.0007642118],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.00005320846,0.001528964,0.2131405,0.00003453672,0.000812895,0.0003129109,0.000008949803,0.0001967657,0.7839113],"genre_scores_gemma":[0.9821273,0.00001436847,0.004129296,0.0001864125,0.0006983701,0.00001770991,0.00001155398,0.00003444506,0.01278052],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9820741,"threshold_uncertainty_score":0.9998352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04778437863520144,"score_gpt":0.2942120461321772,"score_spread":0.2464276674969757,"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."}}