{"id":"W145476732","doi":"10.7202/1029182ar","title":"Musées et médias sociaux","year":2015,"lang":"fr","type":"article","venue":"Documentation et bibliothèques","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Heritage","funders":"","keywords":"Humanities; Political science; Publics; Art","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001305964,0.0006902885,0.0006136488,0.00529825,0.005811242,0.01068585,0.0008882517,0.002316421,0.02119709],"category_scores_gemma":[0.004728273,0.0003765395,0.0003974998,0.008208044,0.01131651,0.008550797,0.004895556,0.002403254,0.00426521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005383146,"about_ca_system_score_gemma":0.00337942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02154025,"about_ca_topic_score_gemma":0.01587159,"domain_scores_codex":[0.9969664,0.001167304,0.0001570917,0.000497809,0.0009140387,0.0002973305],"domain_scores_gemma":[0.9980016,0.0009470806,0.0002804722,0.0002829657,0.0002909821,0.0001968893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004803009,0.00001886819,0.001300506,0.0007993389,0.00001796793,0.0003083143,0.01740042,0.0002786764,0.0004971778,0.8540378,0.02300803,0.102285],"study_design_scores_gemma":[0.000006263063,0.000009921838,0.002383363,0.0007458839,0.000007692276,0.0003046673,0.00619428,0.0001202848,0.0002237174,0.05256811,0.9374134,0.00002235038],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01979655,0.0941067,0.009568995,0.01140873,0.001717895,0.00009281737,0.0009690272,0.0003469129,0.8619924],"genre_scores_gemma":[0.5832646,0.1447475,0.01257376,0.003650869,0.004259237,0.0005104516,0.001670657,0.00036863,0.2489542],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02154025,"threshold_uncertainty_score":0.07091129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1166774037718503,"score_gpt":0.3836151855377355,"score_spread":0.2669377817658852,"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."}}