{"id":"W6907332401","doi":"10.21966/7nwn-bj60","title":"Calliarthron 2023 Experiment - Environmental Data","year":2023,"lang":"en","type":"dataset","venue":"Hakai Institute","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Coralline algae; Ocean acidification; Algae; Marine invertebrates; Invertebrate; Red algae; Biodiversity; Kelp; Crustose","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":[0.005083183,0.001239042,0.002128796,0.001286734,0.0008531258,0.001490778,0.003691683,0.001163053,0.2369294],"category_scores_gemma":[0.007801777,0.0008653693,0.001668492,0.001932361,0.0005538516,0.001173104,0.001548386,0.002621137,0.04858479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001230592,"about_ca_system_score_gemma":0.003566524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02603266,"about_ca_topic_score_gemma":0.04075232,"domain_scores_codex":[0.9980708,0.0006044268,0.00009187828,0.0004423329,0.0004993443,0.0002913216],"domain_scores_gemma":[0.9948145,0.002581788,0.0002498693,0.001338831,0.0007295705,0.0002854648],"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":[0.001964109,0.000240913,0.002914797,0.0007602436,0.0002636792,0.00007959224,0.000124559,0.003198315,0.00175563,0.006616586,0.9583936,0.02368795],"study_design_scores_gemma":[0.002436671,0.0004731304,0.01139612,0.0001899254,0.0002890371,0.00006107701,0.0001133336,0.008348469,0.003344012,0.009631755,0.9635541,0.0001622357],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003066741,0.00006770347,0.01477594,0.0003001924,0.0003729516,0.0007913703,0.9495164,0.01698158,0.01412712],"genre_scores_gemma":[0.03124441,0.0002213574,0.09168573,0.001153447,0.0001158158,0.01852368,0.7971337,0.02673033,0.03319142],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2369294,"threshold_uncertainty_score":0.7926078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09997886419743625,"score_gpt":0.335229451429936,"score_spread":0.2352505872324998,"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."}}