{"id":"W55551993","doi":"","title":"WebGrid II: Developing Hierarchical Knowledge Structures from Flat Grids","year":2000,"lang":"en","type":"article","venue":"","topic":"Cognitive and psychological constructs research","field":"Psychology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Grid; Computer science; Representation (politics); Knowledge representation and reasoning; Value (mathematics); Repertory grid; Theoretical computer science; Data mining; Artificial intelligence; Mathematics; 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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001774216,0.0002520257,0.0002965635,0.0001249536,0.0003276798,0.00006193351,0.0004453786,0.000268861,0.33387],"category_scores_gemma":[0.00005241135,0.0001891386,0.000120009,0.0004019024,0.000317059,0.00007366917,0.0001376714,0.000649685,0.00642327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003301911,"about_ca_system_score_gemma":0.00007443697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002211252,"about_ca_topic_score_gemma":0.00008876021,"domain_scores_codex":[0.9977366,0.0003341751,0.0003375098,0.0007006165,0.0002370242,0.0006540665],"domain_scores_gemma":[0.9987473,0.0004851304,0.00002494926,0.0004100695,0.0000940714,0.0002385185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003235018,0.00007836104,0.003372512,0.000004229098,0.0001339911,0.00007704668,0.001088444,8.848334e-8,0.000522112,0.04930066,0.02958441,0.9155146],"study_design_scores_gemma":[0.001577895,0.000273867,0.2614389,0.0000259133,0.00001978925,0.00005471325,0.000261057,0.00001316251,0.0008750575,0.06085769,0.6740727,0.0005292971],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5353773,0.000553473,0.0002700158,0.000646894,0.0003887277,0.0001465515,0.00004565492,0.0001131745,0.4624583],"genre_scores_gemma":[0.9531231,0.00008943659,0.001907594,0.001474937,0.0007382963,0.00003308994,0.00007725333,0.00002642231,0.04252987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9149854,"threshold_uncertainty_score":0.9943504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0734269111233201,"score_gpt":0.3959512822483555,"score_spread":0.3225243711250354,"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."}}