{"id":"W6946389801","doi":"10.3389/fmars.2022.808055.s002","title":"Data_Sheet_2_Ship Biofouling as a Vector for Non-indigenous Aquatic Species to Canadian Arctic Coastal Ecosystems: A Survey and Modeling-Based Assessment.pdf","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biofouling; Fouling; Abundance (ecology); Wildlife; Arctic; Respondent","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":[0.002933363,0.001042408,0.0005911449,0.005060121,0.002186162,0.002320804,0.002598853,0.000705297,0.06186843],"category_scores_gemma":[0.008361877,0.0008205468,0.00127678,0.009606957,0.0004808423,0.0009096573,0.001186638,0.0007767773,0.01136833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01849409,"about_ca_system_score_gemma":0.04447138,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9887308,"about_ca_topic_score_gemma":0.9897126,"domain_scores_codex":[0.9981823,0.00008326526,0.0001235099,0.0001170593,0.001245723,0.0002481216],"domain_scores_gemma":[0.9865336,0.000902615,0.0005491967,0.0004949461,0.01092242,0.0005970674],"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":[0.0002234814,0.0001488109,0.08510045,0.001904271,0.000130924,0.0001655769,0.000428545,0.004676707,0.0006245791,0.001533189,0.8545755,0.05048799],"study_design_scores_gemma":[0.0002456058,0.00006908338,0.3223941,0.001043905,0.0001117634,0.00009153703,0.001075199,0.005756313,0.001106392,0.0004550249,0.6675072,0.0001439967],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0025625,0.000147399,0.0005766232,0.000221074,0.00003663655,0.0004353176,0.9888504,0.0003143081,0.006855669],"genre_scores_gemma":[0.01913699,0.0009475272,0.008937006,0.0002226014,0.00002583304,0.001375469,0.9546836,0.0002284593,0.0144425],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06186843,"threshold_uncertainty_score":0.2069705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0804945863020196,"score_gpt":0.3235627025034976,"score_spread":0.2430681162014779,"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."}}