{"id":"W7034395941","doi":"","title":"$TMET.V Unlocking the Riches: Torr Metals Inc. (TSX.V: TMET) Aims to Test Untapped Copper and Gold Potential in British Columbia and Ontario, Canada","year":2024,"lang":"en","type":"other","venue":"","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Copper; Torr; Test (biology); Base metal","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":[0.0006744939,0.0006945388,0.0003766591,0.0007722891,0.001832002,0.001990179,0.0009943561,0.001046813,0.1582233],"category_scores_gemma":[0.0007241298,0.0002773683,0.0002721575,0.0005740996,0.0009815355,0.0007246306,0.001389504,0.00110202,0.04137186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005373922,"about_ca_system_score_gemma":0.00537308,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2558666,"about_ca_topic_score_gemma":0.5105031,"domain_scores_codex":[0.9993728,0.00002418187,0.000004596293,0.00004732087,0.0004035126,0.0001475304],"domain_scores_gemma":[0.9992446,0.00003836258,0.00001860364,0.00005968684,0.0004465657,0.0001922776],"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":[0.0003103408,0.0001689433,0.001621034,0.0001353984,0.00001894592,0.000142944,0.00009501594,0.001463602,0.0112963,0.02039525,0.8849784,0.07937372],"study_design_scores_gemma":[0.00006701787,0.0002591636,0.002785842,0.00005893013,0.000009931569,0.00008974929,0.0001685871,0.003361637,0.0100624,0.002461755,0.9806514,0.00002362738],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01297699,0.0005523452,0.005243197,0.002692027,0.000603173,0.0002368285,0.005925615,0.003217831,0.9685521],"genre_scores_gemma":[0.06772187,0.0003521719,0.004128952,0.0004890761,0.00002789055,0.0001044751,0.00455342,0.001001034,0.9216212],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7441334,"threshold_uncertainty_score":0.5293097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00543494274473917,"score_gpt":0.1792172048894978,"score_spread":0.1737822621447586,"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."}}