{"id":"W2907172041","doi":"10.15659/uzalcbs2018.6180","title":"3B YÜZ TANIMADA KİLİT NOKTA TEMELLİ ALGORİTMALARIN KULLANIM OLANAKLARININ ARAŞTIRILMASI VE DOĞRULUK ANALİZİ","year":2018,"lang":"tr","type":"article","venue":"VII. UZAKTAN ALGILAMA VE CBS SEMPOZYUMU UZAL-CBS2018","topic":"Linguistics and Cultural Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Stantec (Canada)","funders":"","keywords":"Mathematics","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":[0.001756022,0.0005909035,0.0004130449,0.0007582508,0.0008589562,0.003675036,0.0007291965,0.0008115956,0.03954052],"category_scores_gemma":[0.00405522,0.0002336225,0.0004791679,0.0007596238,0.0007034859,0.00255648,0.0008517697,0.0008589849,0.009789772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001103988,"about_ca_system_score_gemma":0.001471645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006449605,"about_ca_topic_score_gemma":0.007587823,"domain_scores_codex":[0.9992247,0.0002357012,0.00007528887,0.0001680368,0.0002271295,0.00006915778],"domain_scores_gemma":[0.9985151,0.0005880991,0.0001072326,0.0001688414,0.0005785983,0.00004213809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008348612,0.0001960448,0.01140101,0.001275751,0.0001278222,0.000460855,0.007148738,0.005619035,0.01883707,0.03550189,0.03136217,0.8872348],"study_design_scores_gemma":[0.0001449,0.0005417729,0.07507399,0.001604359,0.0004859413,0.002269859,0.03472093,0.07798969,0.07767169,0.03926093,0.6899616,0.0002743617],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2913785,0.006861868,0.3530782,0.009250096,0.001040229,0.0005900771,0.00452398,0.004783149,0.3284938],"genre_scores_gemma":[0.664692,0.002549139,0.23556,0.0007613978,0.0001421173,0.0003694049,0.002929808,0.000918097,0.09207799],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03954052,"threshold_uncertainty_score":0.1322762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03570884067215464,"score_gpt":0.2579120810104797,"score_spread":0.2222032403383251,"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."}}