{"id":"W2089763102","doi":"10.1007/978-3-540-77004-6_8","title":"A Spatial Web Graph Model with Local Influence Regions","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University; Wilfrid Laurier University; University of British Columbia","funders":"","keywords":"Degree distribution; Preferential attachment; Embedding; Computer science; Exponent; Graph; Metric space; Theoretical computer science; Metric (unit); Range (aeronautics); Degree (music); Node (physics); Complex network; Topology (electrical circuits); Data mining; Mathematics; World Wide Web; Discrete mathematics; Combinatorics; Artificial intelligence; Physics; Engineering","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":[0.0003148225,0.0004615919,0.0004720972,0.000659765,0.0002071025,0.0001476638,0.001048626,0.0001408821,0.00004609186],"category_scores_gemma":[0.000002994803,0.0003888729,0.0001575387,0.0005428958,0.001318364,0.0001729805,0.0003983997,0.0008021467,0.000009101679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001171958,"about_ca_system_score_gemma":0.000463998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002817508,"about_ca_topic_score_gemma":0.0008470987,"domain_scores_codex":[0.9974626,0.00001235551,0.0003718051,0.0009533671,0.0006594597,0.0005404578],"domain_scores_gemma":[0.9983764,0.0001430074,0.0002357746,0.0008663032,0.0002339889,0.00014456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001526002,0.00003142259,0.0009291241,0.000007330672,0.00003331285,0.00001926308,0.000125431,0.633003,0.00002196753,0.04176974,0.00003691525,0.3240072],"study_design_scores_gemma":[0.0001314684,0.0000733179,0.00005747366,0.0002323536,0.00002895448,0.00000556558,1.518117e-7,0.7147713,0.0001499804,0.283693,0.0004062167,0.0004502153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004614802,0.00004646377,0.9908904,0.0000974741,0.00006412118,0.0002560685,0.000009030075,0.0001034689,0.008071508],"genre_scores_gemma":[0.8647252,0.000004187193,0.1343792,0.0003084494,0.0003511799,0.000009416135,0.00001245729,0.00003449272,0.0001754032],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8642637,"threshold_uncertainty_score":0.9998563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01441397415693004,"score_gpt":0.2506808255035327,"score_spread":0.2362668513466026,"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."}}