{"id":"W3081700927","doi":"10.25676/11124/173167","title":"Hydrogeomorphology and steep creek hazard mitigation lexicon: French, English and German","year":2019,"lang":"en","type":"preprint","venue":"Digital Collections of Colorado (Colorado State University)","topic":"Geological Modeling and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canmore Museum and Geoscience Centre","funders":"Horizon 2020 Framework Programme; European Commission","keywords":"German; Lexicon; Hazard; Computer science; Natural language processing; Linguistics; Artificial intelligence; Philosophy","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001312508,0.000300263,0.0006180256,0.0007041358,0.0004759865,0.0002902405,0.0002814989,0.0003321894,0.0003500885],"category_scores_gemma":[0.00008902404,0.0003396977,0.0001591464,0.0008203888,0.0004944587,0.0003727218,0.0003085728,0.000406611,0.00002459262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004503961,"about_ca_system_score_gemma":0.0001948828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001910042,"about_ca_topic_score_gemma":0.01350399,"domain_scores_codex":[0.9982711,0.0001226525,0.0003371228,0.0007042908,0.0002244461,0.0003403621],"domain_scores_gemma":[0.9985934,0.0002472638,0.0003356213,0.0002980706,0.00029967,0.0002259521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006703224,0.0003032449,0.7642545,0.0004760854,0.00109382,0.0002865861,0.002249029,0.2147101,0.0000228537,0.0002776445,0.006814194,0.00884166],"study_design_scores_gemma":[0.007689893,0.006765744,0.3851562,0.0005217181,0.002040326,0.0002025563,0.0052221,0.3812215,0.0001996634,0.03005659,0.1762855,0.004638139],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9750686,0.0002724712,0.0004182804,0.0001792496,0.0003068783,0.0004102863,0.001790057,0.00009489593,0.02145933],"genre_scores_gemma":[0.9843642,0.0004711419,0.00021886,0.00003202922,0.00003200808,8.176519e-7,0.0006722233,0.000007350808,0.01420144],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3790982,"threshold_uncertainty_score":0.9999055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01006725322042286,"score_gpt":0.1811821990038769,"score_spread":0.171114945783454,"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."}}