{"id":"W6899143888","doi":"10.58079/pw5j","title":"Adapter un mémoire universitaire et ses annexes à une lecture sur écran","year":2020,"lang":"fr","type":"article","venue":"Industrias Culturais (Universidade de Coimbra)","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Adapter (computing); Control (management); Identification (biology); Set (abstract data type)","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0001539788,0.0008378354,0.0007212982,0.0001686743,0.0006903337,0.001936671,0.001597703,0.000998061,0.0006258506],"category_scores_gemma":[0.0002994689,0.0007610903,0.0004857185,0.002958997,0.0004751953,0.008695306,0.0008232311,0.001422648,0.0003189918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000478455,"about_ca_system_score_gemma":0.0007813413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004393541,"about_ca_topic_score_gemma":0.0005720694,"domain_scores_codex":[0.9961595,0.0003582707,0.0004071848,0.001157832,0.0006901841,0.001227007],"domain_scores_gemma":[0.9968034,0.0002259139,0.0003548348,0.0005833308,0.0005530689,0.001479468],"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":[0.0003330336,0.0004707336,0.0002490407,0.000169165,0.0008906982,0.00823585,0.05121592,0.006560184,0.00892345,0.2655371,0.5734301,0.08398485],"study_design_scores_gemma":[0.004688868,0.001513389,0.01615362,0.0006761944,0.0004035598,0.001052416,0.01046595,0.01047514,0.006632582,0.001627008,0.9440053,0.002306002],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.09456854,0.003560086,0.006888537,0.7550775,0.001180617,0.0007068342,0.0004873526,0.0007089127,0.1368217],"genre_scores_gemma":[0.9239349,0.000192111,0.000944931,0.009832073,0.000628447,0.000001844093,0.0001368613,0.00005519427,0.06427358],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8293664,"threshold_uncertainty_score":0.999484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1264259021872949,"score_gpt":0.2599782149630222,"score_spread":0.1335523127757273,"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."}}