{"id":"W6963860407","doi":"10.21233/n3dt01","title":"Site 28 (Mott unpublished) pollen surface sample dataset","year":2017,"lang":"en","type":"dataset","venue":"Neotoma Paleoecological Database","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Pollen; Sample (material); Surface (topology); Raw data","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":[],"consensus_categories":[],"category_scores_codex":[0.0007437203,0.001322887,0.0009689567,0.002566397,0.0005197932,0.001517437,0.001636124,0.001311711,0.03164386],"category_scores_gemma":[0.003339838,0.0005085866,0.0009434578,0.004986761,0.000297293,0.0007909664,0.001063196,0.001267097,0.05638451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008720974,"about_ca_system_score_gemma":0.001746833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02338735,"about_ca_topic_score_gemma":0.04588845,"domain_scores_codex":[0.9994231,0.00007328703,0.00005965289,0.0001487645,0.0002189842,0.00007617179],"domain_scores_gemma":[0.9985045,0.0002743875,0.0001561795,0.0003548503,0.0005852562,0.0001247829],"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":[0.0000645411,0.00002656356,0.001746241,0.0004179726,0.00004657445,0.00002789918,0.00002384755,0.0006300793,0.0002705896,0.0003627136,0.9935629,0.002820072],"study_design_scores_gemma":[0.0003481433,0.00002254226,0.01327201,0.0001621423,0.00004261937,0.00005005407,0.00009069416,0.001121053,0.0006786886,0.0009830924,0.9831961,0.00003264513],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002629913,0.00002335717,0.00006625862,0.00001865433,0.0000103569,0.000005969147,0.9989386,0.0001929928,0.000480834],"genre_scores_gemma":[0.000514121,0.00001947781,0.0002187337,0.00001299629,0.000003199604,0.00003064895,0.9987255,0.00005767426,0.0004176531],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03164386,"threshold_uncertainty_score":0.1058593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03245494995724853,"score_gpt":0.3113474159590036,"score_spread":0.2788924660017551,"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."}}