{"id":"W4389322310","doi":"10.36227/techrxiv.24715296","title":"Freestyle Object Localization","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Natural Science Foundation of China","keywords":"Object (grammar); Computer science; Artificial intelligence; Probabilistic logic; Class (philosophy); Annotation; Statistical model; Object model; Pattern recognition (psychology); Function (biology); Machine learning; Computer vision","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":[0.0007728448,0.001470279,0.001511749,0.0008548301,0.0006145581,0.001742168,0.003973181,0.002155773,0.005318478],"category_scores_gemma":[0.002470441,0.0005526909,0.001274644,0.001376342,0.001309473,0.004192126,0.004446505,0.001575784,0.004248363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001021874,"about_ca_system_score_gemma":0.0009833988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006136737,"about_ca_topic_score_gemma":0.006172559,"domain_scores_codex":[0.998835,0.0001436141,0.00004496995,0.0005862274,0.0002313342,0.0001587232],"domain_scores_gemma":[0.9989579,0.0001673862,0.0001014317,0.0005335541,0.0001779366,0.00006178287],"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":[0.000410588,0.0001630054,0.003358858,0.0004412635,0.0001893391,0.0005190496,0.0003388041,0.2320722,0.01876169,0.03946942,0.04391723,0.6603585],"study_design_scores_gemma":[0.00002407302,0.00009315173,0.0007939734,0.00004478792,0.00003588132,0.0004867552,0.00009287648,0.9242481,0.01192623,0.04368687,0.01852499,0.00004224693],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007845845,0.0005985458,0.9822757,0.0002116267,0.00009078025,0.00004400849,0.0004551088,0.006073951,0.002404343],"genre_scores_gemma":[0.4941905,0.00105757,0.4742587,0.0009082533,0.0002355581,0.0002415642,0.005700029,0.001483404,0.02192446],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006136737,"threshold_uncertainty_score":0.01779211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02154001832588602,"score_gpt":0.2332102900809174,"score_spread":0.2116702717550314,"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."}}