{"id":"W4394974142","doi":"","title":"Une image fait un mémoire","year":2018,"lang":"fr","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Diverse Cultural and Historical Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Moiré pattern; Computer science; Image (mathematics); 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":[0.001355874,0.001402118,0.0004733735,0.001128377,0.005372209,0.007432153,0.0006653994,0.003757794,0.05079241],"category_scores_gemma":[0.007155678,0.0002988492,0.0009030831,0.0005335715,0.004666863,0.005474148,0.003084856,0.006692005,0.01110502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002345251,"about_ca_system_score_gemma":0.001362124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004438089,"about_ca_topic_score_gemma":0.003574578,"domain_scores_codex":[0.9983422,0.0005153519,0.00004832623,0.0001716987,0.0007415189,0.0001809447],"domain_scores_gemma":[0.9967964,0.0009312177,0.0001793386,0.000236821,0.001432063,0.0004241443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004342771,0.0001325667,0.0008879003,0.0006610098,0.00007184701,0.006456114,0.04388045,0.0003849866,0.02150241,0.2994495,0.5091725,0.1169664],"study_design_scores_gemma":[0.000008448732,0.0000340606,0.0005187293,0.000144219,0.000007881456,0.002241375,0.004960957,0.0001114562,0.00130681,0.004363029,0.9862751,0.00002791925],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.02463544,0.007933292,0.01461393,0.1011113,0.07561003,0.00009302095,0.0003483151,0.0006506558,0.775004],"genre_scores_gemma":[0.1644802,0.00399698,0.005319872,0.009377639,0.02618859,0.0001092448,0.0001938716,0.0009771592,0.7893565],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05079241,"threshold_uncertainty_score":0.1699175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01951889618654359,"score_gpt":0.2402940345686985,"score_spread":0.2207751383821549,"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."}}