{"id":"W6931837008","doi":"10.5683/sp2/cbf371","title":"Pauline Cove -- Herschel Island -- UAV Photogrammetry -- Point Cloud -- 2019","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"Circadian rhythm and melatonin","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Cove; Photogrammetry; Point cloud; Data set; Point (geometry); Cloud computing","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":[0.000504636,0.002439695,0.001201873,0.001864828,0.000717776,0.001416888,0.001856363,0.001488092,0.02515828],"category_scores_gemma":[0.001648325,0.0005914163,0.00106655,0.003095703,0.0005262942,0.0009880518,0.001632126,0.001328044,0.0627013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008499313,"about_ca_system_score_gemma":0.001374093,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05897914,"about_ca_topic_score_gemma":0.1216493,"domain_scores_codex":[0.999352,0.00005409072,0.00004218483,0.0002018232,0.0002358219,0.0001141205],"domain_scores_gemma":[0.9990973,0.0001082846,0.0000658764,0.0003168313,0.0003094231,0.0001023213],"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":[0.0001096481,0.00004691927,0.002075403,0.0005536628,0.00004746849,0.00007218008,0.00006301624,0.001130686,0.001089452,0.0003454202,0.9871393,0.007326765],"study_design_scores_gemma":[0.0001645443,0.00003861361,0.01905974,0.0002142225,0.00003127299,0.0001319239,0.0002104229,0.001957967,0.002402111,0.0008873882,0.9748263,0.0000754239],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007634307,0.00006795942,0.0002296185,0.00003663693,0.00003545731,0.00001967106,0.9958866,0.001717248,0.001243329],"genre_scores_gemma":[0.0009631977,0.0000295871,0.0004799824,0.00001324068,0.000003893629,0.00002478464,0.9978824,0.0001307999,0.0004720646],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9410208,"threshold_uncertainty_score":0.1172717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01898892179807478,"score_gpt":0.2635239059887211,"score_spread":0.2445349841906463,"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."}}