{"id":"W2916683860","doi":"10.31142/ijtsrd14566","title":"Image Tagging With Social Assistance","year":2018,"lang":"en","type":"article","venue":"International Journal of Trend in Scientific Research and Development","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"ASTER","funders":"","keywords":"Computer science; Computer vision; Artificial intelligence","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":[0.001040593,0.0009220628,0.0005222634,0.002888721,0.001239846,0.001542457,0.0009709455,0.001259576,0.004426026],"category_scores_gemma":[0.002957776,0.0003344437,0.0008537173,0.002284217,0.0006588704,0.002369433,0.001898213,0.0005932449,0.008146321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005706732,"about_ca_system_score_gemma":0.0006208038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002694463,"about_ca_topic_score_gemma":0.005152714,"domain_scores_codex":[0.998717,0.0003837586,0.00005166151,0.0003178968,0.0003963771,0.0001333477],"domain_scores_gemma":[0.9983531,0.0003272471,0.0001503148,0.0006147047,0.0004672339,0.00008742604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004040164,0.0003862565,0.005442956,0.0004281094,0.0001103012,0.0004709567,0.000564133,0.01116343,0.04284884,0.01640921,0.03369132,0.8880804],"study_design_scores_gemma":[0.00007590756,0.00068962,0.0128415,0.0001285923,0.0003085117,0.002371143,0.001186501,0.6755179,0.08272959,0.05533432,0.1685228,0.0002937524],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05416283,0.001528502,0.8882684,0.001025448,0.0006191559,0.000614429,0.001184716,0.007601609,0.04499503],"genre_scores_gemma":[0.5546076,0.001202132,0.3912452,0.0006961417,0.0005883625,0.0002857804,0.002210651,0.000404167,0.04875993],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004426026,"threshold_uncertainty_score":0.01480657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08076619290715345,"score_gpt":0.3934073984828766,"score_spread":0.3126412055757232,"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."}}