{"id":"W4392268123","doi":"","title":"Analyser la disponibilité de l'Information géographique numérique dans les enjeux de suivi et de gestion du trait de côte : application aux cas breton (France) et québécois (Canada)","year":2021,"lang":"fr","type":"preprint","venue":"theses.fr (ABES)","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Cartography; Geographic information system; Environmental resource management; Environmental planning; Environmental science","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"],"consensus_categories":[],"category_scores_codex":[0.01012002,0.0007596256,0.0009075911,0.0004314311,0.001127483,0.0005341391,0.000988815,0.001200828,0.0001012418],"category_scores_gemma":[0.001570482,0.0008222511,0.0005810024,0.001514093,0.0009137254,0.001403748,0.0003287451,0.001423218,0.00001533447],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00338804,"about_ca_system_score_gemma":0.009625235,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9806304,"about_ca_topic_score_gemma":0.9832217,"domain_scores_codex":[0.9920499,0.003189105,0.001504698,0.0006412554,0.001228548,0.001386449],"domain_scores_gemma":[0.9948928,0.001417522,0.001235098,0.0008765912,0.001083308,0.0004946449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00003129976,0.0001010249,0.2107721,0.0005785712,0.000322677,0.00001085919,0.4121782,0.01332517,0.0003213584,0.3580676,0.00009546881,0.004195601],"study_design_scores_gemma":[0.0004416872,0.00004084457,0.6930394,0.0007891411,0.0002058947,0.0001127807,0.2210394,0.006796727,0.0003495399,0.008363417,0.06788205,0.0009390787],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7950677,0.0005744929,0.1308355,0.01751056,0.0003363443,0.001541555,0.0002503832,0.0002704128,0.053613],"genre_scores_gemma":[0.9901317,0.004825543,0.001790311,0.001438079,0.0002751701,0.0009907079,0.0003641823,0.00005618172,0.0001281715],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4822673,"threshold_uncertainty_score":0.9994228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0189792932993449,"score_gpt":0.2855113708409921,"score_spread":0.2665320775416472,"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."}}