{"id":"W6967831095","doi":"10.5281/zenodo.13252738","title":"Notaris scirpi","year":2022,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Botany, Ecology, and Taxonomy Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dragonfly; Range (aeronautics); Mountain range (options); Scirpus; Wetland; Economic shortage","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000107101,0.000686422,0.0002705547,0.002190972,0.002393405,0.000460144,0.0005887948,0.000392778,0.01274522],"category_scores_gemma":[0.0002960178,0.0001765632,0.0001917331,0.001021111,0.0006473637,0.0004855898,0.0006939466,0.0003534358,0.004714933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002229473,"about_ca_system_score_gemma":0.0008403639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1394291,"about_ca_topic_score_gemma":0.3740645,"domain_scores_codex":[0.9998046,0.00001188264,0.00001518037,0.0000648333,0.00006655663,0.00003708202],"domain_scores_gemma":[0.9998552,0.00001308865,0.00004828439,0.000014856,0.00005039222,0.00001818249],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001207106,0.0003524653,0.2173296,0.002379825,0.0001567022,0.01026654,0.007740036,0.001173457,0.1168796,0.004875299,0.04044423,0.5971952],"study_design_scores_gemma":[0.00004148402,0.0002529921,0.7549462,0.0005147716,0.0001023111,0.009276047,0.003164014,0.0003436037,0.004301836,0.0008971865,0.2261101,0.00004934926],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5927162,0.01189185,0.00191526,0.000728664,0.0006751031,0.0003609012,0.006287919,0.0004507154,0.3849733],"genre_scores_gemma":[0.9522896,0.002638798,0.001857047,0.0004054386,0.00008796828,0.00008606558,0.003887405,0.0000316183,0.03871604],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1394291,"threshold_uncertainty_score":0.277235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05055034637233893,"score_gpt":0.2179521352494668,"score_spread":0.1674017888771278,"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."}}