{"id":"W2164159688","doi":"10.1007/s10489-013-0495-8","title":"A trust-based service suggestion system using human plausible reasoning","year":2014,"lang":"en","type":"article","venue":"Applied Intelligence","topic":"Access Control and Trust","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Context (archaeology); Trust management (information system); Service (business); Set (abstract data type); World Wide Web; Function (biology); Domain (mathematical analysis); Trust anchor; Service provider; Computational trust; Value (mathematics); Information retrieval; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002599638,0.0006964868,0.001212033,0.001581857,0.001865066,0.002450085,0.00235673,0.002048649,0.005533278],"category_scores_gemma":[0.01003805,0.0005232582,0.0008340891,0.001015146,0.000674482,0.003681173,0.001589767,0.00151456,0.001788165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0013055,"about_ca_system_score_gemma":0.002155145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01167234,"about_ca_topic_score_gemma":0.01195956,"domain_scores_codex":[0.9982074,0.0004114039,0.0001937086,0.0004438578,0.0006100706,0.0001335087],"domain_scores_gemma":[0.9945974,0.002254721,0.0003608729,0.0009019565,0.001490281,0.0003946495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005574707,0.002366881,0.02117515,0.0008525056,0.0006654864,0.002491057,0.002417103,0.08063536,0.07200492,0.03627986,0.04197231,0.7335646],"study_design_scores_gemma":[0.0001327061,0.0001494071,0.001203663,0.00002525134,0.0001651022,0.0003187774,0.0001691474,0.969437,0.01378212,0.008863474,0.005673806,0.000079529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1075586,0.0004519912,0.8535163,0.001617717,0.0002701538,0.0005248904,0.0004622468,0.02923732,0.006360812],"genre_scores_gemma":[0.7542685,0.0001062973,0.2405179,0.0002559795,0.00007461815,0.0001171928,0.0004803151,0.0002121677,0.00396701],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01167234,"threshold_uncertainty_score":0.0232088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03452102496261754,"score_gpt":0.3152108338700538,"score_spread":0.2806898089074363,"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."}}