{"id":"W2096217132","doi":"10.1145/2556288.2557304","title":"LACES","year":2014,"lang":"en","type":"preprint","venue":"","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Video production; Computer science; Workflow; Video editing; Casual; Multimedia; Video capture; Status quo; Non-linear editing system; Process (computing); CLIPS; Overhead (engineering); Production (economics); Video processing; Computer graphics (images); Smacker video; Artificial intelligence; Database","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002040948,0.00008203123,0.0001407267,0.00007086828,0.0000312711,0.0002943394,0.0008064257,0.00009114556,0.0000481949],"category_scores_gemma":[0.00001870453,0.00006414893,0.00008466143,0.0000824454,0.000006603858,0.00007241507,0.001013167,0.0001096954,0.0001213855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001001779,"about_ca_system_score_gemma":0.00003451637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005281923,"about_ca_topic_score_gemma":0.00002409768,"domain_scores_codex":[0.9992872,0.00004279543,0.0001337752,0.0003001856,0.0001539383,0.00008214328],"domain_scores_gemma":[0.9991739,0.00001981497,0.00007044661,0.0006481044,0.00005455469,0.00003317933],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[6.088269e-7,0.00004411509,0.002453748,0.00006774996,0.00009854166,0.000003229834,0.0002742972,0.01958697,0.00005272177,0.8140569,0.07608258,0.08727854],"study_design_scores_gemma":[0.00002879045,0.00000548795,0.0006102035,0.0000119192,0.000008242057,2.985849e-7,0.000001520355,0.9371893,0.0001619154,0.03791742,0.02392348,0.0001413927],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005288231,0.00004916817,0.9549653,0.001344662,0.0002151426,0.00003453774,2.265953e-7,0.0001438091,0.04271836],"genre_scores_gemma":[0.9093888,0.00003907288,0.07902426,0.0009578532,0.0001576387,0.000008903797,0.00001695891,0.000005376363,0.0104011],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9176024,"threshold_uncertainty_score":0.2838322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01327357366581962,"score_gpt":0.2388602005251291,"score_spread":0.2255866268593095,"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."}}