{"id":"W6945789617","doi":"10.25545/4upj00/z1csxu","title":"finite_difference.m","year":2023,"lang":"en","type":"dataset","venue":"UNB Dataverse","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001139304,0.003872132,0.002530367,0.003138729,0.00114993,0.00404876,0.006019922,0.004033393,0.3510541],"category_scores_gemma":[0.006789086,0.001566138,0.002401363,0.006372459,0.0006741394,0.003090025,0.003677747,0.002939356,0.3767092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001631947,"about_ca_system_score_gemma":0.001739919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01526735,"about_ca_topic_score_gemma":0.01969428,"domain_scores_codex":[0.9990039,0.0001582645,0.00009958305,0.0003372167,0.0002170506,0.0001839436],"domain_scores_gemma":[0.9979159,0.0007361475,0.0001277509,0.0006924107,0.0003001459,0.0002276458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005894871,0.00001491412,0.0001662029,0.0005938805,0.0000235976,0.000009953213,0.00001626019,0.0003267764,0.00006520672,0.0008245096,0.9961861,0.001713661],"study_design_scores_gemma":[0.0005077109,0.00002106455,0.0006962906,0.000318962,0.00002144976,0.00003095577,0.00003082379,0.001200261,0.000396924,0.005272557,0.9914712,0.00003179011],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.00004165325,0.00003968105,0.0001446532,0.00005953253,0.00002287308,0.000006473825,0.996148,0.002632302,0.0009048667],"genre_scores_gemma":[0.0005100783,0.00007474364,0.0006709117,0.0001125144,0.00001197874,0.00008110413,0.9966215,0.001194805,0.0007223647],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.3510541,"threshold_uncertainty_score":0.9256425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04076492812422463,"score_gpt":0.2640192720095489,"score_spread":0.2232543438853243,"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."}}