{"id":"W4256153909","doi":"10.1145/1878061","title":"Proceedings of the 2010 ACM workshop on Social, adaptive and personalized multimedia interaction and access","year":2010,"lang":"en","type":"paratext","venue":"","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Personalization; Computer science; Multimedia; Adaptation (eye); World Wide Web; Context (archaeology); Scalability","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001930594,0.0001988089,0.000326184,0.0001498469,0.0001963004,0.0004648106,0.0008762999,0.0003073292,0.0001977783],"category_scores_gemma":[0.0001266605,0.0001266001,0.00009372198,0.0003230782,0.0001437308,0.0006021674,0.0007260434,0.000511002,0.00002072631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002195004,"about_ca_system_score_gemma":0.0000484849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009515568,"about_ca_topic_score_gemma":0.00007525746,"domain_scores_codex":[0.9988752,0.00002727979,0.0002369239,0.0004356744,0.0002931263,0.0001318111],"domain_scores_gemma":[0.9989445,0.0001555927,0.0003888471,0.0002007985,0.0002635209,0.00004677635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000131463,0.0001787381,0.0006257697,0.0001628164,0.0003626069,5.16578e-7,0.007121602,0.00001206056,0.003374314,0.01051618,0.8104907,0.1670232],"study_design_scores_gemma":[0.006754265,0.0005926242,0.07994759,0.002931635,0.001244375,0.00004561904,0.007555974,0.5737002,0.01787607,0.006531977,0.2979772,0.004842483],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2904389,0.002980681,0.1321412,0.05368321,0.02479477,0.006423547,0.0001760531,0.0004141444,0.4889475],"genre_scores_gemma":[0.5491976,0.003685832,0.02052451,0.002125759,0.001588145,0.0001427239,0.00008010552,0.00009530909,0.42256],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5736881,"threshold_uncertainty_score":0.5162604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05229072121084883,"score_gpt":0.3183892015281524,"score_spread":0.2660984803173036,"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."}}