{"id":"W4213101158","doi":"10.5220/0010816800003122","title":"Dynamic Latent Scale for GAN Inversion","year":2022,"lang":"en","type":"article","venue":"","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Inversion (geology); Computer science; Scale (ratio); Geology; Physics; Geomorphology","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":[0.0001267737,0.00003628491,0.00004581462,0.00005511978,0.0001808825,0.00002972356,0.0002827787,0.000009098941,0.0006247212],"category_scores_gemma":[0.000006551587,0.00003340005,0.00004975769,0.0001234494,0.000005955673,0.00008330432,0.000120429,0.00003205194,0.00006340858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004229368,"about_ca_system_score_gemma":0.00001546134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000778439,"about_ca_topic_score_gemma":0.00000891129,"domain_scores_codex":[0.9995449,0.00002169469,0.0000627124,0.00014735,0.0001239437,0.00009940279],"domain_scores_gemma":[0.9997422,0.0000409956,0.00001732478,0.000145239,0.00001789574,0.00003634036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002185847,0.0002562739,0.0005816314,0.00001557293,0.0000166185,0.00001043419,0.0005469654,0.0001132535,0.006912139,0.01241128,0.04755517,0.9315588],"study_design_scores_gemma":[0.0003701831,0.0001135605,0.000696887,0.000002036238,0.000003725163,0.0000151282,0.0001685102,0.9274963,0.009251659,0.006074511,0.05566003,0.0001474403],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08207636,0.00001593847,0.8898624,0.006624822,0.0007055512,0.0003045069,0.00001060286,0.0003323422,0.02006755],"genre_scores_gemma":[0.8432063,0.000003441377,0.1472455,0.002190809,0.000008050173,0.00007138296,0.000006625494,0.00000518817,0.007262715],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9314114,"threshold_uncertainty_score":0.6840259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01883095066766176,"score_gpt":0.2323575539620046,"score_spread":0.2135266032943428,"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."}}