{"id":"W7132070262","doi":"","title":"Sıralama ve arama algoritmalarının geliştirilmesi","year":2017,"lang":"en","type":"dissertation","venue":"AYBU AVESIS","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute of Steel Construction","keywords":"Headline; Context (archaeology); Sorting","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003836536,0.0003857265,0.0004024726,0.0002453299,0.0005412748,0.000915479,0.002537415,0.0004233379,0.0001107208],"category_scores_gemma":[0.0002670763,0.0003779302,0.0001925406,0.0001720626,0.00003386791,0.0006990607,0.0001045812,0.000555428,0.001279655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005975809,"about_ca_system_score_gemma":0.000220085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001914551,"about_ca_topic_score_gemma":0.00007019691,"domain_scores_codex":[0.9976819,0.0001113707,0.0003896929,0.0008926794,0.0005161144,0.0004082725],"domain_scores_gemma":[0.9964748,0.0001036223,0.0006558393,0.002431205,0.0001807796,0.0001537317],"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":[0.0000174993,0.00007336405,0.0003335844,0.0001554018,0.00007823075,0.00003491906,0.001188784,0.000004195267,0.0005350471,0.01759331,0.02380648,0.9561792],"study_design_scores_gemma":[0.0007782711,0.000176693,0.2651289,0.0004817469,0.0001671546,0.00003248442,0.0002943724,0.01537702,0.005004803,0.004219482,0.706521,0.001818166],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.04106551,0.004519189,0.04790946,0.008068572,0.01432783,0.001606661,0.0001575281,0.002479478,0.8798658],"genre_scores_gemma":[0.4021304,0.001520533,0.06142095,0.00082279,0.002069038,0.0003060549,0.01055977,0.000234489,0.520936],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.954361,"threshold_uncertainty_score":0.9998673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01423835752764654,"score_gpt":0.289551204436753,"score_spread":0.2753128469091065,"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."}}