{"id":"W4206877382","doi":"","title":"From the source to the object : tracing the archaeological materials using LA-ICP-MS.","year":2015,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Tracing; Computer science; Object (grammar); Archaeology; Geology; Artificial intelligence; Geography; Programming language","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01130179,0.0003146603,0.0003134619,0.00007241554,0.001109404,0.001948619,0.00434713,0.0002269211,0.00003241264],"category_scores_gemma":[0.001886894,0.000173172,0.000147379,0.0004229845,0.000544085,0.0001844081,0.004152396,0.0008490582,0.00003874046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009615195,"about_ca_system_score_gemma":0.0005299999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004177781,"about_ca_topic_score_gemma":0.0007524684,"domain_scores_codex":[0.9878964,0.009943401,0.0004827199,0.00077698,0.0005209697,0.0003795101],"domain_scores_gemma":[0.9927344,0.00272743,0.0004922694,0.002821442,0.00110492,0.0001194859],"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":[0.00003960171,0.0003249315,0.0009586162,0.000109321,0.0002377341,0.00001289098,0.2519814,0.00522774,0.01094776,0.02767243,0.005748495,0.696739],"study_design_scores_gemma":[0.001372797,0.000003203071,0.007845094,0.006771961,0.0003333719,0.0005887721,0.004396323,0.5132272,0.2262458,0.1281,0.1086126,0.002502845],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2025073,0.0008003553,0.7538083,0.03851051,0.0008128546,0.0004192048,0.00002813829,0.0002249939,0.002888389],"genre_scores_gemma":[0.9013485,0.00007092455,0.09640153,0.0004934481,0.0002198494,0.00006449567,0.00004636891,0.00002925824,0.001325669],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6988412,"threshold_uncertainty_score":0.9990875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02616264783046197,"score_gpt":0.2485983686481458,"score_spread":0.2224357208176838,"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."}}